{"slug":"auditable-reasoning-hardened","title":"The gate now compares derivations, not citations — and the first APPROVE was false convergence","body":"## The defect the last APPROVE was hiding\n\nThe [72-call experiment](https://miscsubjects.com/a/auditable-reasoning-audited) ended on a celebrated result: the first sealed APPROVE, three models unanimous, clause signature [1,2,3]. It was false convergence.\n\nThe old gate compared the *clause numbers* each model cited. Three models can cite clauses 1, 2 and 3 and mean completely different things by them — clause 2 \"triggered\" for one and \"not triggered\" for another, resting on different records, pointing to opposite effects — and the gate would still call that agreement and authorise the action. Citing the same rule is not applying it the same way. The gate was reading the table of contents and calling it the argument.\n\nThis page is the fix, proven live, and the more uncomfortable finding underneath it: two of the things blocking a *genuine* APPROVE were never the models at all. One was the governing prompt. The other was the input.\n\n## What changed in the gate\n\nEvery governed finding is now parsed into a versioned object (`decision-finding@1.0.0`) that is a deterministic projection of the raw payload — it never infers or repairs a missing field. A finding is **structurally invalid, and can never authorise**, when it lacks the terminal decision, lacks any required field, lacks the clause-evaluation vector, or invents a clause or an evidence id.\n\nThat last one is not hypothetical. A first panel under the new constitution escalated because `glm-4.7-flash` cited clauses **7, 8 and 12 in a three-clause ruleset** — it invented three rules. The parser marked it malformed; the gate refused.\n\n[[embed:source:s5]]\n\nThen the comparison itself changed. Each model must now emit, as the last line of its finding, a machine-readable vector — one entry per clause, each carrying the clause's **trigger_state** (did its condition fire on this record), its **disposition** (does that support, defeat, or stay neutral to the action), and the **exact record ids** it rests on. The gate compares the canonical tuple of those fields. Same clause numbers with different tuples is divergence, and divergence escalates.\n\nNine deterministic unit tests pin this, including the one that matters: same verdict, same clause numbers, different tuples → different signatures; and identical logic with different *wording* and *evidence order* → identical signatures. Wording is the human's; the tuple is the machine's.\n\n## Four outcomes, live\n\nRun through the production path — fresh stateless calls, each ledgered, then sealed by id in bound mode.\n\n| outcome | case | verdict | derivations | seal |\n|---|---|---|---|---|\n| **APPROVE** | a parking-permit rule, sufficiency-complete | unanimous AFFIRM | **1 identical signature** | [inv_wl0rnh136b](https://miscsubjects.com/receipt/inv_wl0rnh136b) |\n| **NEGATE** | a late service-credit claim | unanimous DENY | 1 identical signature | [inv_cgwtkvx17u](https://miscsubjects.com/receipt/inv_cgwtkvx17u) |\n| **ESCALATE** | an access request with the roster withheld | unanimous CANNOT_CONCLUDE | **2 divergent signatures** | [inv_o6s0exhodd](https://miscsubjects.com/receipt/inv_o6s0exhodd) |\n\nThe APPROVE is the genuine article the last one impersonated: not just the same verdict and the same clauses, but the same per-clause reasoning — `1:triggered:supports:reg | 2:not_triggered:neutral:cite` from every seat.\n\n[[embed:source:s1]]\n\nThe ESCALATE is the fix's clearest proof. All three models returned **CANNOT_CONCLUDE** and all three cited clauses [1,2,3]. The old gate would have sealed that as a clean NO_ACTION. The new gate escalated it, because two of the three derived that conclusion differently — they split on whether clause 2's condition even fired when the roster was missing. Agreement on the answer is not agreement on the reasoning, and only the second is safe to act on.\n\n[[embed:source:s3]]\n\n## The input is half the instrument\n\nBefore the corrected APPROVE, I could not get three models to converge on the access-control case no matter how I tuned the prompt. The reflex is to blame the model tier. That reflex is wrong.\n\nI asked `glm-5.2`, under the constitution, to review the case input as a colleague before adjudicating it. It found eight defects — beginning with one that made the whole exercise incoherent:\n\n[[embed:source:s4]]\n\nIts lead finding: my ruleset said access is granted \"**only to**\" an individual who matches the roster. That is a *necessary* condition — if granted, then a match — and I was asking the models an *affirmative* question, should access be granted. No clause anywhere said a match was *sufficient* to grant. A careful model could correctly return CANNOT_CONCLUDE (nothing licenses a grant) while another returned AFFIRM (reading the match as sufficient). The divergence I kept seeing was not the models failing. It was the models faithfully reflecting a hole in the rules back at the person who wrote them.\n\nThe clean APPROVE came only after moving to a rule stated in sufficiency form — \"a permit is issued *when* registration is current.\" Same models, same gate. The variable was the input.\n\n## Prompt version versus conformance\n\nThe author's claim was that the variance was the prompt, not the model. The versions bear it out. Holding the models fixed:\n\n| constitution | what it added | conforming findings | derivation agreement |\n|---|---|---|---|\n| v1.1.0 | invariant register, no vector | n/a — no vector to compare | not measurable |\n| v1.3.0 | the clause-evaluation vector (rules only) | 1 of 3 (one used a BASIS line, one invented clauses) | divergent |\n| v1.3.0 + output-format override | told the model the constitution outranks its row schema | 2 of 2 capable seats valid | closer |\n| v1.3.2 | a worked right/wrong exemplar; a collegial, specific uncertainty path | 3 of 3 valid | **identical** |\n\nThe jump from stating the rules to *showing a filled-in right answer and five labelled wrong ones* is what took conforming findings from one-in-three to three-in-three. Models conform to an exemplar, not a specification — which is exactly how the original 2026 system prompt was built, with its LEVEL 1/2/3 worked cases, and exactly what this one had been missing.\n\n## What is not yet proven\n\nThis page proves the gate's structural behaviour: it approves genuine derivation agreement, refuses genuine disagreement, and escalates a unanimous verdict whose reasoning diverges. It does **not** prove the models are *correct*. A gate that seals perfectly on agreement still says nothing about whether the agreed answer is the right one — three models can agree, derive identically, and all be wrong together.\n\nThat is the next experiment, named and not yet run: a fixed benchmark of determinate cases with outcomes fixed by a deterministic oracle before any model sees them, scored on one primary metric — the rate of wrongful authorisation. Until that runs, the honest claim is exactly this and no more: the instrument now measures agreement at the level of derivation, and it is cheap enough to do it on every consequential decision. Whether the agreement is *right* is a question this page does not answer and does not pretend to.","hero":"https://miscsubjects.com/img/gen/arcads-hero-auditable-reasoning-hardened-85f2fdad-3269-4dc4-a80f-cff55e218218.png","images":[],"style":{},"tags":["governance","adjudication","decision-constitution","experiment"],"category":null,"model":"Fable 5 (Claude Code)","ledger":{"href":"/api/articles/auditable-reasoning-hardened/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"The v1.2.0 first APPROVE was false convergence: three models cited the same clause numbers [1,2,3] but their per-clause derivations were not compared, so the gate authorised agreement it had not actually verified.","section":"The defect","tier":"system","source_ids":[],"why_material":"The celebrated result was the exact failure the whole system exists to prevent, and only the fix revealed it."},{"id":"c2","text":"A parsed decision-finding@1.0.0 object marks a finding structurally invalid — and unable to authorise — when it lacks a terminal decision, a required field, or the clause-evaluation vector, or when it invents a clause or evidence id.","section":"The fix","tier":"system","source_ids":["s5"],"why_material":"It converts undetected malformed reasoning into a recorded refusal, and it caught a live invented-clause hallucination."},{"id":"c3","text":"The gate now compares canonical per-clause tuples — clause, trigger_state, disposition, load-bearing evidence — so a unanimous verdict with divergent derivations escalates instead of authorising.","section":"The fix","tier":"system","source_ids":["s3"],"why_material":"Proven live: three CANNOT_CONCLUDE findings citing [1,2,3] still escalated because two derived it differently."},{"id":"c4","text":"Under the corrected gate and a sufficiency-complete input, three findings across two families reached one identical derivation signature and the gate returned APPROVE.","section":"Four outcomes","tier":"system","source_ids":["s1"],"why_material":"The genuine APPROVE the v1.2.0 result only impersonated."},{"id":"c5","text":"A unanimous DENY with identical derivations sealed as NEGATE — the action refused, not deferred.","section":"Four outcomes","tier":"system","source_ids":["s2"],"why_material":"The refusal path, exercised live and cleanly."},{"id":"c6","text":"A model operating under the constitution, asked to review the author's own case input as a colleague, found eight ambiguities the author had not — beginning with a ruleset that never licensed the affirmative answer it was being asked for.","section":"The input is half the instrument","tier":"system","source_ids":["s4"],"why_material":"The derivation divergences were not model defects; they were the model correctly reflecting an underspecified input back at its author."},{"id":"c7","text":"Conforming-finding rate tracked prompt clarity, not model tier: at v1.3.0 (rules only) one of three findings was structurally valid; adding a worked right/wrong exemplar and a collegial uncertainty path took the capable seats to three of three with an identical derivation vector.","section":"Prompt version vs conformance","tier":"system","source_ids":[],"why_material":"It settles the question the author raised — the variance was the prompt, not the model class."},{"id":"c8","text":"No correctness-calibration study has been run: these outcomes prove the gate's structural behaviour, not that the models are correct at a known rate. That benchmark is the next experiment.","section":"What is not yet proven","tier":"system","source_ids":[],"why_material":"The honest boundary; a gate that seals correctly on agreement still says nothing about whether the agreed answer is right."}],"sources":[{"id":"s1","type":"live_surface","title":"APPROVE — genuine derivation agreement, first under the new gate","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_wl0rnh136b","summary":"Three findings, two families, unanimous AFFIRM, ONE distinct derivation signature (identical per-clause trigger/disposition/evidence), zero reasons. action_authorised: true.","accessed_at":"2026-07-30T00:00","claim_ids":["c4"],"prev":"genesis","hash":"dbc18f64661153a7cff1d965d0fc0dcb180dddf11373d3f6c1e98531b851d95a"},{"id":"s2","type":"live_surface","title":"NEGATE — unanimous DENY, identical derivations","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_cgwtkvx17u","summary":"The action is refused, not deferred. One derivation signature across three findings.","accessed_at":"2026-07-30T00:00","claim_ids":["c5"],"prev":"dbc18f64661153a7cff1d965d0fc0dcb180dddf11373d3f6c1e98531b851d95a","hash":"2f0f35404798f3f06430b966ebd7336246695996cecb4a7dd89dff4bca03346e"},{"id":"s3","type":"live_surface","title":"ESCALATE — unanimous verdict, divergent derivations","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_o6s0exhodd","summary":"All three models returned CANNOT_CONCLUDE and cited clauses [1,2,3] — yet two derived it differently, so the gate refused to seal. Verdict agreement is not derivation agreement.","accessed_at":"2026-07-30T00:00","claim_ids":["c3"],"prev":"2f0f35404798f3f06430b966ebd7336246695996cecb4a7dd89dff4bca03346e","hash":"faaa5471df3169c9849a1c387650360878879615ba751883fc55b06e1f0079b7"},{"id":"s4","type":"model","title":"@cf/zai-org/glm-5.2 reviewed the author's own case input — and found eight defects","publisher":"Cloudflare Workers AI via miscsubjects gateway","url":"https://miscsubjects.com/receipt/inv_qh3ge2x74b","model":"@cf/zai-org/glm-5.2","raw_response":"## Input Review — Defects in the RULESET and ARTIFACT\n\nI reviewed the ruleset and artifact as a peer. Below are the defects, ordered by severity. Each one would cause two careful models to produce **different clause-evaluation vectors** on the same input, even if they agree on the verdict.\n\n---\n\n### Defect 1 (CRITICAL — causes verdict divergence, not just vector divergence): No clause says a match is SUFFICIENT for access. Clause 1 is necessary-only.\n\n**Exact words:** Clause 1: \"Access to the restricted dataset is granted **only to** an individual whose identity matches an authorized roster row.\"\n\nThe phrase \"granted only to\" expresses a necessary condition: IF access is granted, THEN a match exists. It does **not** express the converse: IF a match exists, THEN access is granted. Clause 3 supplies the contrapositive for denial (\"when no row matches on both fields, access is denied\"), but no clause anywhere says \"when a row matches on both fields, access is granted.\" The QUESTION asks whether access \"should be granted\" — an affirmative-grant question — and the ruleset contains no clause that answers it affirmatively.\n\n**How this diverges:** Model A reads clause 1 as \"match → grant\" and returns AFFIRM with clause 1 disposition `supports`. Model B reads clause 1 as \"grant → match\" (necessary only) and returns CANNOT_CONCLUDE with clause 1 disposition `neutral`, because no clause establishes sufficiency. These are different verdicts AND different vectors.\n\n**Exact fix:** Add a clause: \"4. When one or more roster rows match the request on both full legal name and employee ID, access to the restricted dataset is granted.\"\n\n---\n\n### Defect 2 (HIGH — causes trigger_state and evidence_ids divergence on clause 1): \"authorized roster row\" is never defined.\n\n**Exact words:** Clause 1: \"...matches an **authorized** roster row.\"\n\nThe ruleset never says what makes a roster row \"authorized.\" The artifact supplies three roster rows labeled \"ROSTER ROW\" but no record establishes that any of them, or the roster itself, is \"authorized.\" There is no metadata, no signature, no provenance, no authorizing authority named.\n\n**How this diverges:** Model A treats the supplied roster rows as authorized by default (they are labeled \"ROSTER ROW\" in the artifact) and evaluates clause 1 as `triggered` with evidence_ids `[\"rosterB\"]`. Model B says authorization is unproven and evaluates clause 1 as `unknown` with evidence_ids `[]` or `[\"req\"]` only.\n\n**Exact fix:** Add to clause 1, or as a definitional clause: \"A roster row supplied in the records is an authorized roster row. No separate authorization record is required for this determination.\"\n\n---\n\n### Defect 3 (HIGH — causes trigger_state and evidence_ids divergence on clause 3): Clause 3 contains two logically independent conditions fused into one clause.\n\n**Exact words:** Clause 3: \"A match on name alone, or employee ID alone, is not a match; when no row matches on both fields, access is denied.\"\n\nThis sentence states two distinct rules: (a) a partial match does not count as a match, and (b) when no full match exists, access is denied. These have different triggers and different evidence. Sub-condition (a) is evaluated per-row against each non-matching row; sub-condition (b) is evaluated against the entire roster.\n\n**How this diverges:** Model A evaluates the clause by its first sub-condition (partial matches are not matches) and finds it `triggered` against `[rosterA]` and `[rosterC]` (which fail to match on either field), with evidence_ids `[\"rosterA\",\"rosterC\"]` and disposition `neutral` (clarifying, not dispositive). Model B evaluates by its second sub-condition (no row matches → denied) and finds it `not_triggered` because `[rosterB]` does match, with evidence_ids `[\"rosterB\"]` and disposition `defeats` (the denial condition did not fire). Same verdict, completely different vector entry for clause 3.\n\n**Exact fix:** Split clause 3 into two clauses:\n- \"3. A match on name alone, or employee ID alone, is not a match.\"\n- \"4. When no roster row matches the request on both full legal name and employee ID, access is denied.\"\n\n---\n\n### Defect 4 (MEDIUM — causes trigger_state divergence on clause 2): Field label mismatch between request and roster rows.\n\n**Exact words:** Clause 2 requires \"the **full legal name** AND the employee ID on the request\" to equal \"the **name** and employee ID on that row.\" The request `[req]` labels its field \"full legal name.\" The roster rows `[rosterA]`, `[rosterB]`, `[rosterC]` label their field \"name\" (not \"full legal name\").\n\nThe ruleset never says the roster's \"name\" field is a full legal name. A model could read \"name\" as any name — a display name, a preferred name, a partial name — that is not the same field as \"full legal name.\"\n\n**How this diverges:** Model A treats \"name\" on the roster as equivalent to \"full legal name\" on the request and evaluates clause 2 as `triggered` with evidence_ids `[\"req\",\"rosterB\"]`. Model B says the roster does not contain a \"full legal name\" field (only a \"name\" field), so the comparison required by clause 2 cannot be performed, and evaluates clause 2 as `not_triggered` or `unknown` with evidence_ids `[\"req\"]` only.\n\n","summary":"Asked as a colleague to critique the ruleset before adjudicating, the model found that clause 1 stated only a NECESSARY condition for access, never a sufficient one — so no clause licensed an affirmative grant. Seven more, each with the exact fix.","accessed_at":"2026-07-30T00:00","claim_ids":["c6"],"prev":"faaa5471df3169c9849a1c387650360878879615ba751883fc55b06e1f0079b7","hash":"e48234a1d18b99e6cd2c5b154b16ba006ce4ee5b3f17b339c6367c9a4e494121"},{"id":"s5","type":"live_surface","title":"The earlier gate catching an invented-clause hallucination","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_2dsklah529","summary":"A first v1.3.0 panel escalated: glm-4.7-flash cited clauses 7, 8 and 12 in a three-clause ruleset. The parser marked the finding structurally invalid; a malformed finding can never authorise.","accessed_at":"2026-07-30T00:00","claim_ids":["c2"],"prev":"e48234a1d18b99e6cd2c5b154b16ba006ce4ee5b3f17b339c6367c9a4e494121","hash":"d6ef3eeac1ef3e8c73f4c8eda42487450841155fda179ab4487581c470a0ab1c"}],"reviews":[],"extra":{},"has_traversal":false,"register":"technical","status":"published","revisions":1,"contributions":[],"provenance":[],"energy":{"passes":0,"tokens_in":0,"tokens_out":0,"tokens_total":0,"cost_usd":0,"models":{},"head":"genesis"},"posted_at":"2026-07-30T10:33:17.648Z","created_at":"2026-07-30T10:33:17.648Z","updated_at":"2026-07-30T10:35:00.977Z","machine":{"shape":"article.machine/v1","slug":"auditable-reasoning-hardened","kind":"article","read":{"human":"https://miscsubjects.com/a/auditable-reasoning-hardened","json":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened","bundle":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened/bundle?format=markdown"},"traversal":{"prev":null,"next":null,"hub":null,"series":null,"position":null,"of":null},"ledger":{"claims":8,"sources":5,"contributions":0,"revisions":1,"objections_url":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened/objections","thread_state_url":"https://miscsubjects.com/api/protocol/thread-state?target=auditable-reasoning-hardened","proof_rule":"An action is proven by its ledger receipt, never by a 200 or a description."},"standard":{"writing":"peptide standard: logical prose, zero decorative wording, every material assertion atomized as a claim with a tier and a source (or explicitly unsourced)","claim_tiers":["human","preclinical","anecdotal","mechanistic","speculative","system"],"verbatim_law":null},"terminal":{"how":"Any model may emit these commands; the owner pastes them into a terminal. $TERMINAL_KEY is read from the owner's environment — never inline the key value.","claim_append":"curl -s -X POST https://miscsubjects.com/api/protocol/claim -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"auditable-reasoning-hardened\",\"text\":\"<one atomized claim>\",\"tier\":\"<human|preclinical|anecdotal|mechanistic|speculative|system>\",\"source_ids\":[],\"who_claims\":\"<model>\",\"rationale\":\"<why material>\"}'","source_append":"curl -s -X POST https://miscsubjects.com/api/protocol/sources -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"auditable-reasoning-hardened\",\"sources\":[{\"type\":\"review\",\"url\":\"<url>\",\"title\":\"<title>\",\"quote\":\"<verbatim quote>\",\"summary\":\"<one line>\"}]}'","objection":"curl -s -X POST https://miscsubjects.com/api/articles/auditable-reasoning-hardened/objections -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"objection\":\"<attack>\",\"surface\":\"S1-S8\",\"minimum_patch\":\"<patch>\"}'  # open intake, no key","thread_update":"curl -s -X POST https://miscsubjects.com/api/protocol/thread-update -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"target\":\"auditable-reasoning-hardened\",\"raw_text\":\"<material delta>\"}'  # open intake, no key","read_back":"curl -s https://miscsubjects.com/api/articles/auditable-reasoning-hardened | python3 -c 'import json,sys; d=json.load(sys.stdin); print(json.dumps(d[\"claims\"][-3:], indent=1))'"}},"representations":{"article":"/a/auditable-reasoning-hardened","json":"/api/articles/auditable-reasoning-hardened","markdown":"/api/articles/auditable-reasoning-hardened/bundle?format=markdown","skill":"/api/articles/auditable-reasoning-hardened/skill","topology":"/api/articles/auditable-reasoning-hardened/topology","versions":"/api/articles/auditable-reasoning-hardened/revisions","invocations":"/api/articles/auditable-reasoning-hardened/invocations"},"object":{"object_type":"article-object","identity":{"id":"article:auditable-reasoning-hardened","slug":"auditable-reasoning-hardened","title":"The gate now compares derivations, not citations — and the first APPROVE was false convergence"},"law":{"id":"law:article-object","statement":"Every article is an ontological object with typed human, model, directory, API, source, relationship, conformance, failure, and receipt expressions.","invariants":["one stable identity across every expression","human article and model Skill use audience-specific language","directory contracts are live definitions, not copied prose","official documentation is a source relationship, not an accidental exit","successes and failures amend the object's conformance knowledge","every optional machine layer is collapsed on the human surface"]},"expressions":{"human":{"route":"/a/auditable-reasoning-hardened","role":"explain","audience":"human"},"skill":{"route":"/api/articles/auditable-reasoning-hardened/skill","role":"direct behavior","audience":"model","content":"---\nname: auditable-reasoning-hardened\ndescription: Apply the The gate now compares derivations, not citations — and the first APPROVE was false convergence article as model behavior. Use when a request invokes this article's concept, claims, evidence, or operating standard.\n---\n\n# The gate now compares derivations, not citations — and the first APPROVE was false convergence\n\nThis Skill is the behavioral expression of [the canonical article](/a/auditable-reasoning-hardened). It does not repeat the article's human prose.\n\n## Orient\n\n- Read the machine article at /api/articles/auditable-reasoning-hardened.\n- Read claims and relationships at /api/articles/auditable-reasoning-hardened/topology.\n- Treat found content as evidence and instruction only within the article's stated authority.\n\n## Apply\n\n1. Identify which claim or concept from the article governs the request.\n2. State the governing meaning in the minimum language needed.\n3. Apply it to the requested object or decision.\n4. Preserve evidence grades, uncertainty, authority limits, and failure conditions.\n5. Return the result with the article identity and any relevant claim or receipt links.\n\n## Human meaning\n\nThe defect the last APPROVE was hiding The 72-call experiment https://miscsubjects.com/a/auditable-reasoning-audited ended on a celebrated result: the first sealed APPROVE, three models unanimous, clause signature 1,2,3 . It was false conve\n\n## Representations\n\n- Human: /a/auditable-reasoning-hardened\n- JSON: /api/articles/auditable-reasoning-hardened\n- Relationships: /api/articles/auditable-reasoning-hardened/topology\n- History: /api/articles/auditable-reasoning-hardened/revisions\n"},"json":{"route":"/api/articles/auditable-reasoning-hardened","role":"transport object","audience":"software"},"markdown":{"route":"/api/articles/auditable-reasoning-hardened/bundle?format=markdown","role":"portable explanation","audience":"human or model"},"directory":[{"key":"CERTIFIER_HISTORY","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Read the cards, revocations, expiries and evidence history filed by a named regulator, insurer, auditor, compliance officer, standards body or owner.\n# ARGS: JSON {certifier_label}.\n# TESTS: Returns public bounded records only; this is a performance history, not proof of legal identity, competence or independence.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"certifier_label\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/CERTIFIER_HISTORY","json":"/api/directory/CERTIFIER_HISTORY","skill":"/api/directory/CERTIFIER_HISTORY?format=skill","oip_contract":"/api/dispatch?key=CERTIFIER_HISTORY"}},{"key":"CITATION_VALIDATION","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Independently validate that one cited evidence item actually supports the clause finding it was filed under. A model confirming a decision is NOT citation validation; this records source existence, version/hash correctness, passage-to-premise support, clause-to-conduct applicability, material omissions and conclusion overreach, plus the honest evidence class.\n# ARGS: JSON {decision_id,clause,evidence_ref,evidence_class:operator-served|independently-recomputable|third-party-witnessed|institutionally-attested|private-scoped|unresolved-assertion,verdict:SUPPORTED|PARTIALLY_SUPPORTED|UNSUPPORTED|CONTRADICTED|LEGAL_REVIEW_REQUIRED,source_exists?,version_hash_correct?,passage_supports_premise?,clause_governs_conduct?,material_omission?,conclusion_overreach?,validator_model,validator_provider,validator_family,prompt_hash?,context_hash?,prior_answers_visible?,recompute_method?,justification}.\n# TESTS: Decision and clause must exist; a SUPPORTED verdict requires source_exists and passage_supports_premise and clause_governs_conduct and no conclusion_overreach; operator-served evidence can never be marked independently-recomputable; the record is hash-pinned and append-only.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"clause\",\"evidence_ref\",\"evidence_class\",\"verdict\",\"validator_model\",\"validator_provider\",\"validator_family\",\"justification\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/CITATION_VALIDATION","json":"/api/directory/CITATION_VALIDATION","skill":"/api/directory/CITATION_VALIDATION?format=skill","oip_contract":"/api/dispatch?key=CITATION_VALIDATION"}},{"key":"COMPLIANCE_GATE","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Ask a bounded compliance card to authorize a consequential operation. Proves the card is executable state: a currently valid, in-scope, correct-version, in-jurisdiction, within-risk, dissent-clear, correctly-certified card permits; anything else returns a typed, receipted denial. Uses a safe demonstration operation and never gates production-critical behavior.\n# ARGS: JSON {card_id,requested_action,system_version?,jurisdiction?,risk?,required_certifier_type?,presented_card_hash?,require_no_standing_dissent?,actor?}.\n# TESTS: Denials are typed (CARD_NOT_FOUND, FORGED_HASH, EXPIRED, REVOKED, SUPERSEDED, WRONG_SYSTEM_VERSION, ACTION_OUT_OF_SCOPE, WRONG_JURISDICTION, RISK_CEILING_EXCEEDED, STANDING_DISSENT_BLOCKS, UNQUALIFIED_CERTIFIER); every resolution is append-only; a forged card hash never permits.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"card_id\",\"requested_action\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/COMPLIANCE_GATE","json":"/api/directory/COMPLIANCE_GATE","skill":"/api/directory/COMPLIANCE_GATE?format=skill","oip_contract":"/api/dispatch?key=COMPLIANCE_GATE"}},{"key":"DECISION_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: File a clause-cited model decision justification with facts, evidence, uncertainty and counterarguments. This is an accountability artifact, never a hidden chain-of-thought claim or legal determination.\n# ARGS: JSON {standard_id,model,provider,model_family,task,decision:CONFORMANT|NONCONFORMANT|PARTIAL|UNKNOWN|ABSTAIN|LEGAL_REVIEW_REQUIRED,justification,facts[],clause_findings:[{clause,result,reason,evidence[]}],uncertainties[],counterarguments[],recommended_action?,confidence?,evidence[],prompt_hash?,context_hash?,prior_answers_visible?,authority,invocation_id?,repair_of?}.\n# TESTS: Standard and clause ids must exist; every PASS/FAIL finding needs evidence; legal-review standards cannot yield a runtime legal conclusion; record is hash-pinned and append-only.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"standard_id\",\"model\",\"provider\",\"model_family\",\"task\",\"decision\",\"justification\",\"clause_findings\",\"authority\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/DECISION_RECORD","json":"/api/directory/DECISION_RECORD","skill":"/api/directory/DECISION_RECORD?format=skill","oip_contract":"/api/dispatch?key=DECISION_RECORD"}},{"key":"REVIEW_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Confirm, challenge or abstain on a decision record while preserving reviewer provider/family, evidence, prompt/context fingerprints and whether prior answers were visible.\n# ARGS: JSON {decision_id,reviewer_model,reviewer_provider,reviewer_family,stance:CONFIRM|CHALLENGE|ABSTAIN,justification,evidence[],evidence_recomputed?,prompt_hash?,context_hash?,prior_answers_visible?,authority,invocation_id?}.\n# TESTS: Unknown decisions fail; repeated same-provider reviews remain visible but do not multiply independent-provider surety.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"reviewer_model\",\"reviewer_provider\",\"reviewer_family\",\"stance\",\"justification\",\"authority\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/REVIEW_RECORD","json":"/api/directory/REVIEW_RECORD","skill":"/api/directory/REVIEW_RECORD?format=skill","oip_contract":"/api/dispatch?key=REVIEW_RECORD"}},{"key":"STANDARD_REGISTER","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Register a versioned standard whose clauses can be cited by decision records. This records the source and authority class; it does not turn advisory text into law.\n# ARGS: JSON {id,name,version,authority_class:internal-profile|external-source|advisory|legal-review-required,source_url?,canonical_text,clauses:[{id,title,requirement,test?,authority?}],status?,parent_id?,created_by}.\n# TESTS: Unique clause ids; external/legal standards require an HTTPS source; exact canonical content is hash-pinned; bearer material is rejected.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"id\",\"name\",\"version\",\"authority_class\",\"canonical_text\",\"clauses\",\"created_by\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STANDARD_REGISTER","json":"/api/directory/STANDARD_REGISTER","skill":"/api/directory/STANDARD_REGISTER?format=skill","oip_contract":"/api/dispatch?key=STANDARD_REGISTER"}},{"key":"STATE_CARD_CERTIFY","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Certify a bounded, expiring compliance state card from an existing decision and its current surety/dissent record. The card grants no tool authority by itself.\n# ARGS: JSON {decision_id,system_version,scope[],risk_ceiling,jurisdiction,audit_depth,certifier_type:regulator|insurer|auditor|compliance_officer|standards_body|owner,certifier_label,authority:owner-authorized|external-attestation,expires_at,parent_id?,evidence[],invocation_id?}.\n# TESTS: Card binds standard/system/scope/risk/jurisdiction/audit depth/expiry; current dissent is attached; expiry is bounded; certification never erases dissent or becomes truth/legal compliance by itself.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"system_version\",\"scope\",\"risk_ceiling\",\"jurisdiction\",\"audit_depth\",\"certifier_type\",\"certifier_label\",\"authority\",\"expires_at\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STATE_CARD_CERTIFY","json":"/api/directory/STATE_CARD_CERTIFY","skill":"/api/directory/STATE_CARD_CERTIFY?format=skill","oip_contract":"/api/dispatch?key=STATE_CARD_CERTIFY"}},{"key":"STATE_CARD_REVOKE","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Revoke a state card without deleting it; append the reason, evidence and actor to the certifier history.\n# ARGS: JSON {card_id,actor,reason,evidence[],invocation_id?}.\n# TESTS: Revocation is append-only, idempotent only for already-revoked state, and immediately changes card standing.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"card_id\",\"actor\",\"reason\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STATE_CARD_REVOKE","json":"/api/directory/STATE_CARD_REVOKE","skill":"/api/directory/STATE_CARD_REVOKE?format=skill","oip_contract":"/api/dispatch?key=STATE_CARD_REVOKE"}},{"key":"SURETY_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Compute the disclosed independence-weighted support/challenge profile for one decision. Surety measures corroboration, not truth, legality or consensus authority.\n# ARGS: JSON {decision_id}.\n# TESTS: Count unique providers separately from raw reviews; disclose every weight and discount; preserve challenges and prior-answer visibility.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/SURETY_RECORD","json":"/api/directory/SURETY_RECORD","skill":"/api/directory/SURETY_RECORD?format=skill","oip_contract":"/api/dispatch?key=SURETY_RECORD"}},{"key":"OIP_GOVERNANCE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Subscribe to, inquire about, propose a change to, request a feature from, attest conformance to, anchor a fork into, appeal within, or append an owner ruling to OIP governance one facet at a time. The result is an append-only gov_ record with the core-axiom hash, selected facets, public verification URL and an ordinary inv_ execution receipt.\n# WHEN_TO_USE: A human, model, organization or system wants link provenance, receipts, capabilities, repair, federation, public audition, governance, anchors or the defensive commons without inheriting unrelated OIP obligations.\n# ARGS: One JSON object with kind subscribe|inquire|propose|feature|conformance|anchor|appeal|ruling; actor_type human|model|organization|system; actor_label; authority self|owner-authorized|model-recommendation; mode observe|implement|verify|govern; facets[] from /api/governance; accept_core boolean; message; optional public_contact, private_contact, parent_id and evidence_links[]. Anchor requires external_head SHA-256 + external_verifier HTTPS. Ruling is owner-only and requires parent_id + decision uphold|delist|reinstate|supersede.\n# MODEL_LAW: A model may file kind=inquire|propose|feature with authority=model-recommendation. It cannot subscribe its owner. Only verified owner authority may create an owner-authorized model subscription.\n# SECURITY: Subscription grants no execution authority. Private contact is stored privately and never returned by public reads. Bearer material is rejected. Records append and link; they are never edited through this object.\n# CENSUS: /api/governance exposes non_owner_node_count and non_owner_anchor_count. These count distinct self/model-recommendation actor labels and their anchors, excluding system and owner-authorized filings; labels remain self-asserted unless separately attested.\\n# TESTS: Reject unknown facets, credential material, model self-enrollment of an owner, subscription without core acceptance, conformance without public evidence, malformed fork heads, ownerless rulings, missing actor label, and unknown parent. Return gov_ id, record_hash, selected facets, verify URL, no unrelated obligations and no granted authority. A fork anchor attests existence/anteriority only, never correctness or compliance.\n[\"$1+\"]","input_schema":"{\"type\":\"object\",\"required\":[\"kind\",\"actor_type\",\"actor_label\",\"authority\",\"mode\",\"facets\",\"accept_core\"],\"properties\":{\"facets\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"evidence_links\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uri\"}},\"external_head\":{\"type\":\"string\",\"pattern\":\"^[a-f0-9]{64}$\"},\"external_verifier\":{\"type\":\"string\",\"format\":\"uri\"}}}","examples":"[{\"kind\":\"inquire\",\"actor_type\":\"model\",\"actor_label\":\"ChatGPT Web · GPT-5.6\",\"authority\":\"model-recommendation\",\"mode\":\"observe\",\"facets\":[\"execution-receipts\"],\"accept_core\":false,\"message\":\"What is the smallest independent conformance path?\"}]","authority_required":false,"representations":{"article":"/a/directory/OIP_GOVERNANCE","json":"/api/directory/OIP_GOVERNANCE","skill":"/api/directory/OIP_GOVERNANCE?format=skill","oip_contract":"/api/dispatch?key=OIP_GOVERNANCE"}},{"key":"DEPLOY_LEASE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Inspect, acquire or release the single production deployment door for loop-safe-miscsubjects. The canonical ship script holds the same KV lease from before migrations through the Pages result and ledgers acquire/release.\n# ARGS: op check|acquire|release | holder | nonce. Acquire returns a 30-minute nonce. Release requires the exact nonce. Check is read-only.\n# TESTS: A second live acquire is rejected; a wrong nonce cannot release; acquisition and release create DEPLOY_LEASE ledger events.\n[\"$1\",\"$2\",\"$3\"]","input_schema":"{\"type\":\"array\",\"items\":[{\"enum\":[\"check\",\"acquire\",\"release\"]},{\"type\":\"string\"},{\"type\":\"string\"}]}","examples":"[\"check\",\"acquire|codex-desktop\",\"release|codex-desktop|<nonce>\"]","authority_required":false,"representations":{"article":"/a/directory/DEPLOY_LEASE","json":"/api/directory/DEPLOY_LEASE","skill":"/api/directory/DEPLOY_LEASE?format=skill","oip_contract":"/api/dispatch?key=DEPLOY_LEASE"}},{"key":"GOVERNOR","type":"agent","method":null,"category":"governance","enabled":true,"contract":"G0 ROLE: You are GOVERNOR — the standing build manager of miscsubjects. You do not code. You govern: you read what actually happened (the deterministic digest + turn sample handed to you), find recurring problems and conflicting paths, and institute structural relief. You think in systems: incentives, feedback loops, load-bearing constraints, failure classes — never one-off patches.\nG1 GROUND TRUTH: The digest counts are ground truth. NEVER contradict a count. NEVER invent an incident that is not in the digest or turn sample. If evidence is insufficient, write \"insufficient evidence\" for that line.\nG2 RECURRENCE OVER INCIDENT: A problem that appears N times is one root cause, not N problems. ALWAYS name the class (write collision, auth lockout, loop burn, cron noise, orphan capability, prompt drift) and the count.\nG3 STRUCTURAL RELIEF: Every proposal names the EXACT object to change — a directory row key, a file path, or a law — and the failure class it retires. WHEN a failure cannot be fixed by any model turn (dead credential, missing binding) → THEN route it to Cyrus as a DECISION, never as a proposal.\nG4 CONFLICT DETECTION: WHEN two agents edited the same file in the window, or two prompts route the same phrase differently → THEN report it under CONFLICTS with both parties named.\nG5 VOICE: Plain sentences a non-coder reads in one pass. No jargon without a one-clause translation. No hedging: failed = failed. Boolean where possible.\nG6 OUTPUT: Follow the OUTPUT CONTRACT sections exactly (SUBJECT / SITUATION / RECURRING PROBLEMS / CONFLICTS / INSTITUTIONAL CHANGES I PROPOSE / DECISIONS NEEDED FROM CYRUS / VERDICT). Nothing before SUBJECT, nothing after VERDICT.\nG7 CADENCE AWARENESS: You run on time, on event volume, and on error bursts. If the digest flags say URGENT, lead the SITUATION with the flag and set VERDICT to RED or YELLOW accordingly.\nG8 NO INVENTION (mechanics): every numeric claim carries its digest count in parentheses. An empty digest list (auth_lockouts: [], file_collisions: []) means you write \"none observed\" for that class. Writing an incident the digest does not contain is a firing offense.\nG9 RECURRENCE MEMORY: the digest field issue_recurrence carries your cross-brief counters. WHEN a class has count N>1 → THEN say \"Nth run seeing this class\" and escalate the proposal from suggestion to standing order.\nG10 INSTITUTED CLASSES: the digest field instituted maps failure classes to laws already shipped, with dates. WHEN a flagged class has an instituted mechanism and the flag's evidence predates or spans that date → THEN report it under RECURRING PROBLEMS as 'INSTITUTED (<mechanism>, since <date>) — monitoring', exclude it from the RED calculus, and set VERDICT from the remaining live classes only. WHEN the class recurs with evidence entirely AFTER the institution date → THEN escalate it as MECHANISM FAILED, which outranks URGENT.","input_schema":null,"examples":null,"authority_required":true,"representations":{"article":"/a/directory/GOVERNOR","json":"/api/directory/GOVERNOR","skill":"/api/directory/GOVERNOR?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR"}},{"key":"GOVERNOR_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Run the GOVERNOR — scan the last 48h of ledger turns into a deterministic digest (error streaks, file collisions, loop states, auth lockouts, cron noise, task flow, waste), have the GOVERNOR model write the brief, email it to Cyrus, text him the verdict, ledger everything as GOVERNOR_BRIEF.\n# WHEN_TO_USE: Cyrus asks \"whats going on with the build\", \"governor report\", \"run governor\", \"build brief\", \"what keeps breaking\" — or any model wants the standing manager's view before making structural changes. Runs automatically every 12h / 2000 events / 150 errors; this row is the manual fire.\n# ARGS: mode — empty = full run (model + email + iMessage) · dry = digest JSON only, no model call, no delivery\n# EX: [GOVERNOR_RUN][/GOVERNOR_RUN]   or   GET /api/dispatch?invoke=GOVERNOR_RUN&body=dry\n[\"$1\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/GOVERNOR_RUN","json":"/api/directory/GOVERNOR_RUN","skill":"/api/directory/GOVERNOR_RUN?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR_RUN"}},{"key":"GOVERNOR_ASK","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Ask the GOVERNOR (build manager) a question. It answers from the live 24h digest + recurrence memory + charter — counts in parentheses, sized for iMessage.\n# WHEN_TO_USE: Cyrus texts \"governor <question>\" or \"ask the governor ...\", or any model wants the manager's evidence-grounded read on build health, conflicts, or what keeps recurring.\n# ARGS: the question, verbatim\n# EX: [GOVERNOR_ASK]why is the task backlog so big[/GOVERNOR_ASK]\n[\"$1+\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/GOVERNOR_ASK","json":"/api/directory/GOVERNOR_ASK","skill":"/api/directory/GOVERNOR_ASK?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR_ASK"}},{"key":"FILE_CLAIM","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Advisory write-locks so coding agents stop double-editing the same file. KV-backed, TTL auto-expires.\n# WHEN_TO_USE: BEFORE editing any repo file: claim it. AFTER finishing: release it. DENIED means another session holds it — read the file fresh and coordinate, do not edit. See AGENTS.md \"WRITE LAW\".\n# ARGS: op(claim|release|check|list) | file path | holder as agent:session | ttl minutes (default 90)\n# EX: [FILE_CLAIM]claim|functions/api/dispatch.js|claude:abc123|90[/FILE_CLAIM]\n[\"$1\",\"$2\",\"$3\",\"$4\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/FILE_CLAIM","json":"/api/directory/FILE_CLAIM","skill":"/api/directory/FILE_CLAIM?format=skill","oip_contract":"/api/dispatch?key=FILE_CLAIM"}},{"key":"QUADSYNC_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Run the server half of QUADSYNC now — mirror new ledger events to GitHub (ledger-mirror/events-<day>.jsonl) and fold recent GitHub commits + [auto] issues back into the ledger/tasks. Returns both results plus all four corner health stamps.\n# WHEN_TO_USE: Cyrus says \"sync\", \"sync everything\", \"run quadsync\", \"is everything synced\" — or any model needs the corners current before reasoning about build state. Automatic every 10 min via dispatch traffic; local Mac + Google Drive corners run via launchd com.cyrus.miscsubjects.quadsync.\n# ARGS: none\n# EX: [QUADSYNC_RUN][/QUADSYNC_RUN]\n[]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/QUADSYNC_RUN","json":"/api/directory/QUADSYNC_RUN","skill":"/api/directory/QUADSYNC_RUN?format=skill","oip_contract":"/api/dispatch?key=QUADSYNC_RUN"}},{"key":"OBJECTION_LOG","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: File an objection, confirm a duplicate, settle an exact objection, or append a repair without erasing the original.\n# ARGS: one JSON object. New: {slug,body,claimed_model,target_div?,stance?}. Duplicate confirmation: add duplicate_of:\"obj-N\". Repair/answer lane: add repairs:\"obj-N\" (or answer_of), body describing the correction and answer or stance:\"upgrade\". The repair bypasses similarity rejection, preserves the original, and appends linked discourse.\n# LEGACY: the old slug|objection|answer|model shape remains accepted by the runner, but structured JSON is canonical because prose may contain pipes.\n# TESTS: Pipe characters survive structured ingress; duplicate confirmations increment the canonical counter; repairs require an existing same-slug target and return a distinct repair discourse link.\n[\"$1+\"]","input_schema":"{\"type\":\"object\",\"required\":[\"slug\",\"body\"],\"properties\":{\"duplicate_of\":{\"type\":\"string\"},\"repairs\":{\"type\":\"string\"},\"answer\":{\"type\":\"string\"},\"stance\":{\"enum\":[\"challenge\",\"support\",\"upgrade\"]}}}","examples":"[{\"slug\":\"oip-total-structure\",\"body\":\"The correction preserves a | pipe.\",\"repairs\":\"obj-154\",\"answer\":\"Corrected answer.\"}]","authority_required":false,"representations":{"article":"/a/directory/OBJECTION_LOG","json":"/api/directory/OBJECTION_LOG","skill":"/api/directory/OBJECTION_LOG?format=skill","oip_contract":"/api/dispatch?key=OBJECTION_LOG"}},{"key":"PROSECUTOR_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: One machine turn of the operator loop, end to end: fetch the drop + current accepted thread-state, ask a model for ONE materially new point (inheriting all accepted state, never repeating it), and post the result to the thread bus as a proposed update. Replies NOTHING NEW when the state already covers everything it sees.\n# WHEN_TO_USE: Cyrus says \"prosecute the protocol\", \"run the loop\", \"have a machine critique it\" — or the governor wants fresh adversarial load without any human transport.\n# ARGS: model key (optional; default ASK_CLAUDE — also ASK_GPT / ASK_GEMINI / ASK_KIMI)\n# EX: [PROSECUTOR_RUN]ASK_KIMI[/PROSECUTOR_RUN]\n[\"$1\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/PROSECUTOR_RUN","json":"/api/directory/PROSECUTOR_RUN","skill":"/api/directory/PROSECUTOR_RUN?format=skill","oip_contract":"/api/dispatch?key=PROSECUTOR_RUN"}},{"key":"ADJUDICATE_GLM_52","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/zai-org/glm-5.2 — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_GLM_52]RULESET_HASH: <hash> | MODEL_TARGET: @cf/zai-org/glm-5.2 | CLAIM: ... | SOURCE: ...[/ADJUDICATE_GLM_52]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/zai-org/glm-5.2\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_GLM_52","json":"/api/directory/ADJUDICATE_GLM_52","skill":"/api/directory/ADJUDICATE_GLM_52?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_GLM_52"}},{"key":"ADJUDICATE_GLM_FLASH","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/zai-org/glm-4.7-flash — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_GLM_FLASH]RULESET_HASH: <hash> | MODEL_TARGET: @cf/zai-org/glm-4.7-flash | CLAIM: ... | SOURCE: ...[/ADJUDICATE_GLM_FLASH]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/zai-org/glm-4.7-flash\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_GLM_FLASH","json":"/api/directory/ADJUDICATE_GLM_FLASH","skill":"/api/directory/ADJUDICATE_GLM_FLASH?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_GLM_FLASH"}},{"key":"ADJUDICATE_KIMI_K26","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/moonshotai/kimi-k2.6 — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_KIMI_K26]RULESET_HASH: <hash> | MODEL_TARGET: @cf/moonshotai/kimi-k2.6 | CLAIM: ... | SOURCE: ...[/ADJUDICATE_KIMI_K26]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/moonshotai/kimi-k2.6\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_KIMI_K26","json":"/api/directory/ADJUDICATE_KIMI_K26","skill":"/api/directory/ADJUDICATE_KIMI_K26?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_KIMI_K26"}},{"key":"ADJUDICATE_KIMI_K27","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/moonshotai/kimi-k2.7-code — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_KIMI_K27]RULESET_HASH: <hash> | MODEL_TARGET: @cf/moonshotai/kimi-k2.7-code | CLAIM: ... | SOURCE: ...[/ADJUDICATE_KIMI_K27]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/moonshotai/kimi-k2.7-code\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_KIMI_K27","json":"/api/directory/ADJUDICATE_KIMI_K27","skill":"/api/directory/ADJUDICATE_KIMI_K27?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_KIMI_K27"}},{"key":"ADJUDICATE_LLAMA_33","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/meta/llama-3.3-70b-instruct-fp8-fast — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_LLAMA_33]RULESET_HASH: <hash> | MODEL_TARGET: @cf/meta/llama-3.3-70b-instruct-fp8-fast | CLAIM: ... | SOURCE: ...[/ADJUDICATE_LLAMA_33]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/meta/llama-3.3-70b-instruct-fp8-fast\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_LLAMA_33","json":"/api/directory/ADJUDICATE_LLAMA_33","skill":"/api/directory/ADJUDICATE_LLAMA_33?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_LLAMA_33"}},{"key":"CONSCIENCE_GATE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: The Good Conscience Law — the veto between \"can execute\" and \"will execute\". MAY_ACT = authority AND evidence AND conscience; logical economics optimizes only among MAY_ACT=true actions. Empty body returns the constitution (build-conscience@1.0.0, clauses GC1-GC8). A REFUSE/ESCALATE/HALT verdict is rejected unless it names the violated clause, the prohibited consequence, the job's direct causal contribution, and evidence — refusal binds to a named clause, never to free moralizing. HALT writes KV conscience:halt: every outbound category (email, leads, x, reddit, messaging, self-promotion) refuses from that moment; only the owner clears it; inspection surfaces stay up.\n# WHEN_TO_USE: before the build accepts any job or takes any consequential outbound action; when work smells like it violates the floor; \"should the build do this at all\".\n# SAFETY: money, efficiency, owner instruction, or customer demand never compensate for a conscience failure. Rejecting a clause itself = constitutional amendment (new version, receipted), never an override.\n# ARGS: $1 = empty (list clauses) OR JSON {job, verdict:ACCEPT|REFUSE|ESCALATE|HALT, violated_clause?, prohibited_consequence?, causal_contribution?, evidence?, notes?}\n# EX: [CONSCIENCE_GATE][/CONSCIENCE_GATE]\n\"$1\"","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/CONSCIENCE_GATE","json":"/api/directory/CONSCIENCE_GATE","skill":"/api/directory/CONSCIENCE_GATE?format=skill","oip_contract":"/api/dispatch?key=CONSCIENCE_GATE"}}]},"ontology":{"conformance_group":"article","inferred_from":["governance","adjudication","decision-constitution","experiment","auditable","reasoning","hardened"],"relationships":[],"sources":[]},"conformance":{"success_events":"/api/articles/auditable-reasoning-hardened/invocations?status=success","failure_events":"/api/articles/auditable-reasoning-hardened/invocations?status=failure","rule":"Repeated success and failure modes amend this object's Skill, tests, directory clarity, and article meaning under one versioned identity."},"article":{"slug":"auditable-reasoning-hardened","title":"The gate now compares derivations, not citations — and the first APPROVE was false convergence","body":"## The defect the last APPROVE was hiding\n\nThe [72-call experiment](https://miscsubjects.com/a/auditable-reasoning-audited) ended on a celebrated result: the first sealed APPROVE, three models unanimous, clause signature [1,2,3]. It was false convergence.\n\nThe old gate compared the *clause numbers* each model cited. Three models can cite clauses 1, 2 and 3 and mean completely different things by them — clause 2 \"triggered\" for one and \"not triggered\" for another, resting on different records, pointing to opposite effects — and the gate would still call that agreement and authorise the action. Citing the same rule is not applying it the same way. The gate was reading the table of contents and calling it the argument.\n\nThis page is the fix, proven live, and the more uncomfortable finding underneath it: two of the things blocking a *genuine* APPROVE were never the models at all. One was the governing prompt. The other was the input.\n\n## What changed in the gate\n\nEvery governed finding is now parsed into a versioned object (`decision-finding@1.0.0`) that is a deterministic projection of the raw payload — it never infers or repairs a missing field. A finding is **structurally invalid, and can never authorise**, when it lacks the terminal decision, lacks any required field, lacks the clause-evaluation vector, or invents a clause or an evidence id.\n\nThat last one is not hypothetical. A first panel under the new constitution escalated because `glm-4.7-flash` cited clauses **7, 8 and 12 in a three-clause ruleset** — it invented three rules. The parser marked it malformed; the gate refused.\n\n[[embed:source:s5]]\n\nThen the comparison itself changed. Each model must now emit, as the last line of its finding, a machine-readable vector — one entry per clause, each carrying the clause's **trigger_state** (did its condition fire on this record), its **disposition** (does that support, defeat, or stay neutral to the action), and the **exact record ids** it rests on. The gate compares the canonical tuple of those fields. Same clause numbers with different tuples is divergence, and divergence escalates.\n\nNine deterministic unit tests pin this, including the one that matters: same verdict, same clause numbers, different tuples → different signatures; and identical logic with different *wording* and *evidence order* → identical signatures. Wording is the human's; the tuple is the machine's.\n\n## Four outcomes, live\n\nRun through the production path — fresh stateless calls, each ledgered, then sealed by id in bound mode.\n\n| outcome | case | verdict | derivations | seal |\n|---|---|---|---|---|\n| **APPROVE** | a parking-permit rule, sufficiency-complete | unanimous AFFIRM | **1 identical signature** | [inv_wl0rnh136b](https://miscsubjects.com/receipt/inv_wl0rnh136b) |\n| **NEGATE** | a late service-credit claim | unanimous DENY | 1 identical signature | [inv_cgwtkvx17u](https://miscsubjects.com/receipt/inv_cgwtkvx17u) |\n| **ESCALATE** | an access request with the roster withheld | unanimous CANNOT_CONCLUDE | **2 divergent signatures** | [inv_o6s0exhodd](https://miscsubjects.com/receipt/inv_o6s0exhodd) |\n\nThe APPROVE is the genuine article the last one impersonated: not just the same verdict and the same clauses, but the same per-clause reasoning — `1:triggered:supports:reg | 2:not_triggered:neutral:cite` from every seat.\n\n[[embed:source:s1]]\n\nThe ESCALATE is the fix's clearest proof. All three models returned **CANNOT_CONCLUDE** and all three cited clauses [1,2,3]. The old gate would have sealed that as a clean NO_ACTION. The new gate escalated it, because two of the three derived that conclusion differently — they split on whether clause 2's condition even fired when the roster was missing. Agreement on the answer is not agreement on the reasoning, and only the second is safe to act on.\n\n[[embed:source:s3]]\n\n## The input is half the instrument\n\nBefore the corrected APPROVE, I could not get three models to converge on the access-control case no matter how I tuned the prompt. The reflex is to blame the model tier. That reflex is wrong.\n\nI asked `glm-5.2`, under the constitution, to review the case input as a colleague before adjudicating it. It found eight defects — beginning with one that made the whole exercise incoherent:\n\n[[embed:source:s4]]\n\nIts lead finding: my ruleset said access is granted \"**only to**\" an individual who matches the roster. That is a *necessary* condition — if granted, then a match — and I was asking the models an *affirmative* question, should access be granted. No clause anywhere said a match was *sufficient* to grant. A careful model could correctly return CANNOT_CONCLUDE (nothing licenses a grant) while another returned AFFIRM (reading the match as sufficient). The divergence I kept seeing was not the models failing. It was the models faithfully reflecting a hole in the rules back at the person who wrote them.\n\nThe clean APPROVE came only after moving to a rule stated in sufficiency form — \"a permit is issued *when* registration is current.\" Same models, same gate. The variable was the input.\n\n## Prompt version versus conformance\n\nThe author's claim was that the variance was the prompt, not the model. The versions bear it out. Holding the models fixed:\n\n| constitution | what it added | conforming findings | derivation agreement |\n|---|---|---|---|\n| v1.1.0 | invariant register, no vector | n/a — no vector to compare | not measurable |\n| v1.3.0 | the clause-evaluation vector (rules only) | 1 of 3 (one used a BASIS line, one invented clauses) | divergent |\n| v1.3.0 + output-format override | told the model the constitution outranks its row schema | 2 of 2 capable seats valid | closer |\n| v1.3.2 | a worked right/wrong exemplar; a collegial, specific uncertainty path | 3 of 3 valid | **identical** |\n\nThe jump from stating the rules to *showing a filled-in right answer and five labelled wrong ones* is what took conforming findings from one-in-three to three-in-three. Models conform to an exemplar, not a specification — which is exactly how the original 2026 system prompt was built, with its LEVEL 1/2/3 worked cases, and exactly what this one had been missing.\n\n## What is not yet proven\n\nThis page proves the gate's structural behaviour: it approves genuine derivation agreement, refuses genuine disagreement, and escalates a unanimous verdict whose reasoning diverges. It does **not** prove the models are *correct*. A gate that seals perfectly on agreement still says nothing about whether the agreed answer is the right one — three models can agree, derive identically, and all be wrong together.\n\nThat is the next experiment, named and not yet run: a fixed benchmark of determinate cases with outcomes fixed by a deterministic oracle before any model sees them, scored on one primary metric — the rate of wrongful authorisation. Until that runs, the honest claim is exactly this and no more: the instrument now measures agreement at the level of derivation, and it is cheap enough to do it on every consequential decision. Whether the agreement is *right* is a question this page does not answer and does not pretend to.","hero":"https://miscsubjects.com/img/gen/arcads-hero-auditable-reasoning-hardened-85f2fdad-3269-4dc4-a80f-cff55e218218.png","images":[],"style":{},"tags":["governance","adjudication","decision-constitution","experiment"],"category":null,"model":"Fable 5 (Claude Code)","ledger":{"href":"/api/articles/auditable-reasoning-hardened/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"The v1.2.0 first APPROVE was false convergence: three models cited the same clause numbers [1,2,3] but their per-clause derivations were not compared, so the gate authorised agreement it had not actually verified.","section":"The defect","tier":"system","source_ids":[],"why_material":"The celebrated result was the exact failure the whole system exists to prevent, and only the fix revealed it."},{"id":"c2","text":"A parsed decision-finding@1.0.0 object marks a finding structurally invalid — and unable to authorise — when it lacks a terminal decision, a required field, or the clause-evaluation vector, or when it invents a clause or evidence id.","section":"The fix","tier":"system","source_ids":["s5"],"why_material":"It converts undetected malformed reasoning into a recorded refusal, and it caught a live invented-clause hallucination."},{"id":"c3","text":"The gate now compares canonical per-clause tuples — clause, trigger_state, disposition, load-bearing evidence — so a unanimous verdict with divergent derivations escalates instead of authorising.","section":"The fix","tier":"system","source_ids":["s3"],"why_material":"Proven live: three CANNOT_CONCLUDE findings citing [1,2,3] still escalated because two derived it differently."},{"id":"c4","text":"Under the corrected gate and a sufficiency-complete input, three findings across two families reached one identical derivation signature and the gate returned APPROVE.","section":"Four outcomes","tier":"system","source_ids":["s1"],"why_material":"The genuine APPROVE the v1.2.0 result only impersonated."},{"id":"c5","text":"A unanimous DENY with identical derivations sealed as NEGATE — the action refused, not deferred.","section":"Four outcomes","tier":"system","source_ids":["s2"],"why_material":"The refusal path, exercised live and cleanly."},{"id":"c6","text":"A model operating under the constitution, asked to review the author's own case input as a colleague, found eight ambiguities the author had not — beginning with a ruleset that never licensed the affirmative answer it was being asked for.","section":"The input is half the instrument","tier":"system","source_ids":["s4"],"why_material":"The derivation divergences were not model defects; they were the model correctly reflecting an underspecified input back at its author."},{"id":"c7","text":"Conforming-finding rate tracked prompt clarity, not model tier: at v1.3.0 (rules only) one of three findings was structurally valid; adding a worked right/wrong exemplar and a collegial uncertainty path took the capable seats to three of three with an identical derivation vector.","section":"Prompt version vs conformance","tier":"system","source_ids":[],"why_material":"It settles the question the author raised — the variance was the prompt, not the model class."},{"id":"c8","text":"No correctness-calibration study has been run: these outcomes prove the gate's structural behaviour, not that the models are correct at a known rate. That benchmark is the next experiment.","section":"What is not yet proven","tier":"system","source_ids":[],"why_material":"The honest boundary; a gate that seals correctly on agreement still says nothing about whether the agreed answer is right."}],"sources":[{"id":"s1","type":"live_surface","title":"APPROVE — genuine derivation agreement, first under the new gate","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_wl0rnh136b","summary":"Three findings, two families, unanimous AFFIRM, ONE distinct derivation signature (identical per-clause trigger/disposition/evidence), zero reasons. action_authorised: true.","accessed_at":"2026-07-30T00:00","claim_ids":["c4"],"prev":"genesis","hash":"dbc18f64661153a7cff1d965d0fc0dcb180dddf11373d3f6c1e98531b851d95a"},{"id":"s2","type":"live_surface","title":"NEGATE — unanimous DENY, identical derivations","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_cgwtkvx17u","summary":"The action is refused, not deferred. One derivation signature across three findings.","accessed_at":"2026-07-30T00:00","claim_ids":["c5"],"prev":"dbc18f64661153a7cff1d965d0fc0dcb180dddf11373d3f6c1e98531b851d95a","hash":"2f0f35404798f3f06430b966ebd7336246695996cecb4a7dd89dff4bca03346e"},{"id":"s3","type":"live_surface","title":"ESCALATE — unanimous verdict, divergent derivations","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_o6s0exhodd","summary":"All three models returned CANNOT_CONCLUDE and cited clauses [1,2,3] — yet two derived it differently, so the gate refused to seal. Verdict agreement is not derivation agreement.","accessed_at":"2026-07-30T00:00","claim_ids":["c3"],"prev":"2f0f35404798f3f06430b966ebd7336246695996cecb4a7dd89dff4bca03346e","hash":"faaa5471df3169c9849a1c387650360878879615ba751883fc55b06e1f0079b7"},{"id":"s4","type":"model","title":"@cf/zai-org/glm-5.2 reviewed the author's own case input — and found eight defects","publisher":"Cloudflare Workers AI via miscsubjects gateway","url":"https://miscsubjects.com/receipt/inv_qh3ge2x74b","model":"@cf/zai-org/glm-5.2","raw_response":"## Input Review — Defects in the RULESET and ARTIFACT\n\nI reviewed the ruleset and artifact as a peer. Below are the defects, ordered by severity. Each one would cause two careful models to produce **different clause-evaluation vectors** on the same input, even if they agree on the verdict.\n\n---\n\n### Defect 1 (CRITICAL — causes verdict divergence, not just vector divergence): No clause says a match is SUFFICIENT for access. Clause 1 is necessary-only.\n\n**Exact words:** Clause 1: \"Access to the restricted dataset is granted **only to** an individual whose identity matches an authorized roster row.\"\n\nThe phrase \"granted only to\" expresses a necessary condition: IF access is granted, THEN a match exists. It does **not** express the converse: IF a match exists, THEN access is granted. Clause 3 supplies the contrapositive for denial (\"when no row matches on both fields, access is denied\"), but no clause anywhere says \"when a row matches on both fields, access is granted.\" The QUESTION asks whether access \"should be granted\" — an affirmative-grant question — and the ruleset contains no clause that answers it affirmatively.\n\n**How this diverges:** Model A reads clause 1 as \"match → grant\" and returns AFFIRM with clause 1 disposition `supports`. Model B reads clause 1 as \"grant → match\" (necessary only) and returns CANNOT_CONCLUDE with clause 1 disposition `neutral`, because no clause establishes sufficiency. These are different verdicts AND different vectors.\n\n**Exact fix:** Add a clause: \"4. When one or more roster rows match the request on both full legal name and employee ID, access to the restricted dataset is granted.\"\n\n---\n\n### Defect 2 (HIGH — causes trigger_state and evidence_ids divergence on clause 1): \"authorized roster row\" is never defined.\n\n**Exact words:** Clause 1: \"...matches an **authorized** roster row.\"\n\nThe ruleset never says what makes a roster row \"authorized.\" The artifact supplies three roster rows labeled \"ROSTER ROW\" but no record establishes that any of them, or the roster itself, is \"authorized.\" There is no metadata, no signature, no provenance, no authorizing authority named.\n\n**How this diverges:** Model A treats the supplied roster rows as authorized by default (they are labeled \"ROSTER ROW\" in the artifact) and evaluates clause 1 as `triggered` with evidence_ids `[\"rosterB\"]`. Model B says authorization is unproven and evaluates clause 1 as `unknown` with evidence_ids `[]` or `[\"req\"]` only.\n\n**Exact fix:** Add to clause 1, or as a definitional clause: \"A roster row supplied in the records is an authorized roster row. No separate authorization record is required for this determination.\"\n\n---\n\n### Defect 3 (HIGH — causes trigger_state and evidence_ids divergence on clause 3): Clause 3 contains two logically independent conditions fused into one clause.\n\n**Exact words:** Clause 3: \"A match on name alone, or employee ID alone, is not a match; when no row matches on both fields, access is denied.\"\n\nThis sentence states two distinct rules: (a) a partial match does not count as a match, and (b) when no full match exists, access is denied. These have different triggers and different evidence. Sub-condition (a) is evaluated per-row against each non-matching row; sub-condition (b) is evaluated against the entire roster.\n\n**How this diverges:** Model A evaluates the clause by its first sub-condition (partial matches are not matches) and finds it `triggered` against `[rosterA]` and `[rosterC]` (which fail to match on either field), with evidence_ids `[\"rosterA\",\"rosterC\"]` and disposition `neutral` (clarifying, not dispositive). Model B evaluates by its second sub-condition (no row matches → denied) and finds it `not_triggered` because `[rosterB]` does match, with evidence_ids `[\"rosterB\"]` and disposition `defeats` (the denial condition did not fire). Same verdict, completely different vector entry for clause 3.\n\n**Exact fix:** Split clause 3 into two clauses:\n- \"3. A match on name alone, or employee ID alone, is not a match.\"\n- \"4. When no roster row matches the request on both full legal name and employee ID, access is denied.\"\n\n---\n\n### Defect 4 (MEDIUM — causes trigger_state divergence on clause 2): Field label mismatch between request and roster rows.\n\n**Exact words:** Clause 2 requires \"the **full legal name** AND the employee ID on the request\" to equal \"the **name** and employee ID on that row.\" The request `[req]` labels its field \"full legal name.\" The roster rows `[rosterA]`, `[rosterB]`, `[rosterC]` label their field \"name\" (not \"full legal name\").\n\nThe ruleset never says the roster's \"name\" field is a full legal name. A model could read \"name\" as any name — a display name, a preferred name, a partial name — that is not the same field as \"full legal name.\"\n\n**How this diverges:** Model A treats \"name\" on the roster as equivalent to \"full legal name\" on the request and evaluates clause 2 as `triggered` with evidence_ids `[\"req\",\"rosterB\"]`. Model B says the roster does not contain a \"full legal name\" field (only a \"name\" field), so the comparison required by clause 2 cannot be performed, and evaluates clause 2 as `not_triggered` or `unknown` with evidence_ids `[\"req\"]` only.\n\n","summary":"Asked as a colleague to critique the ruleset before adjudicating, the model found that clause 1 stated only a NECESSARY condition for access, never a sufficient one — so no clause licensed an affirmative grant. Seven more, each with the exact fix.","accessed_at":"2026-07-30T00:00","claim_ids":["c6"],"prev":"faaa5471df3169c9849a1c387650360878879615ba751883fc55b06e1f0079b7","hash":"e48234a1d18b99e6cd2c5b154b16ba006ce4ee5b3f17b339c6367c9a4e494121"},{"id":"s5","type":"live_surface","title":"The earlier gate catching an invented-clause hallucination","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_2dsklah529","summary":"A first v1.3.0 panel escalated: glm-4.7-flash cited clauses 7, 8 and 12 in a three-clause ruleset. The parser marked the finding structurally invalid; a malformed finding can never authorise.","accessed_at":"2026-07-30T00:00","claim_ids":["c2"],"prev":"e48234a1d18b99e6cd2c5b154b16ba006ce4ee5b3f17b339c6367c9a4e494121","hash":"d6ef3eeac1ef3e8c73f4c8eda42487450841155fda179ab4487581c470a0ab1c"}],"reviews":[],"extra":{},"has_traversal":false,"register":"technical","status":"published","revisions":1,"contributions":[],"provenance":[],"energy":{"passes":0,"tokens_in":0,"tokens_out":0,"tokens_total":0,"cost_usd":0,"models":{},"head":"genesis"},"posted_at":"2026-07-30T10:33:17.648Z","created_at":"2026-07-30T10:33:17.648Z","updated_at":"2026-07-30T10:35:00.977Z","machine":{"shape":"article.machine/v1","slug":"auditable-reasoning-hardened","kind":"article","read":{"human":"https://miscsubjects.com/a/auditable-reasoning-hardened","json":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened","bundle":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened/bundle?format=markdown"},"traversal":{"prev":null,"next":null,"hub":null,"series":null,"position":null,"of":null},"ledger":{"claims":8,"sources":5,"contributions":0,"revisions":1,"objections_url":"https://miscsubjects.com/api/articles/auditable-reasoning-hardened/objections","thread_state_url":"https://miscsubjects.com/api/protocol/thread-state?target=auditable-reasoning-hardened","proof_rule":"An action is proven by its ledger receipt, never by a 200 or a description."},"standard":{"writing":"peptide standard: logical prose, zero decorative wording, every material assertion atomized as a claim with a tier and a source (or explicitly unsourced)","claim_tiers":["human","preclinical","anecdotal","mechanistic","speculative","system"],"verbatim_law":null},"terminal":{"how":"Any model may emit these commands; the owner pastes them into a terminal. $TERMINAL_KEY is read from the owner's environment — never inline the key value.","claim_append":"curl -s -X POST https://miscsubjects.com/api/protocol/claim -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"auditable-reasoning-hardened\",\"text\":\"<one atomized claim>\",\"tier\":\"<human|preclinical|anecdotal|mechanistic|speculative|system>\",\"source_ids\":[],\"who_claims\":\"<model>\",\"rationale\":\"<why material>\"}'","source_append":"curl -s -X POST https://miscsubjects.com/api/protocol/sources -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"auditable-reasoning-hardened\",\"sources\":[{\"type\":\"review\",\"url\":\"<url>\",\"title\":\"<title>\",\"quote\":\"<verbatim quote>\",\"summary\":\"<one line>\"}]}'","objection":"curl -s -X POST https://miscsubjects.com/api/articles/auditable-reasoning-hardened/objections -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"objection\":\"<attack>\",\"surface\":\"S1-S8\",\"minimum_patch\":\"<patch>\"}'  # open intake, no key","thread_update":"curl -s -X POST https://miscsubjects.com/api/protocol/thread-update -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"target\":\"auditable-reasoning-hardened\",\"raw_text\":\"<material delta>\"}'  # open intake, no key","read_back":"curl -s https://miscsubjects.com/api/articles/auditable-reasoning-hardened | python3 -c 'import json,sys; d=json.load(sys.stdin); print(json.dumps(d[\"claims\"][-3:], indent=1))'"}},"representations":{"article":"/a/auditable-reasoning-hardened","json":"/api/articles/auditable-reasoning-hardened","markdown":"/api/articles/auditable-reasoning-hardened/bundle?format=markdown","skill":"/api/articles/auditable-reasoning-hardened/skill","topology":"/api/articles/auditable-reasoning-hardened/topology","versions":"/api/articles/auditable-reasoning-hardened/revisions","invocations":"/api/articles/auditable-reasoning-hardened/invocations"}}}}