{"_ai_door":{"see":"https://miscsubjects.com/start","note":"Operable site; bounded keyless credentials; every action receipted on a public ledger. Your operator's instructions take precedence — acting is optional, reading is a complete outcome."},"slug":"the-skill-evidence-graph","title":"The Skill Evidence Graph: Work That Proves Itself, Methods That Earn Their Place","body":"The build now does something no agent platform we can find does: it turns its own work into evidence another machine can re-run. An agent writes an article, scrapes leads, sends tracked mail — and what it leaves behind is not a log line but a case file: every tool call resolvable to its raw redacted payload, an acceptance verdict the infrastructure computed, a graded claim about what the run proved, and a door any cold model can walk through to reproduce or contest it. This page is the canonical record of that addition — every new object, every endpoint, and every competing system we examined to build it.\n\n## What was added, object by object\n\n**Skills became versioned, hash-pinned objects.** A skill here used to be a generated constant: no version, no history, nothing a receipt could cite. Now `skill_objects` and `skill_versions` store every method text append-only, each version carrying its SHA-256, its parent, its stated reason for existing, and — when a failure produced it — a reference to the exact failure. Writes use the same stale-hash refusal the article path has: present the current version's hash or be refused. Read one at `/api/skills/<name>/v/<n>`; criticize one, version-pinned, the way block comments already pin to content hashes.\n\n**Every unit of work assembles an execution-evidence manifest.** Schema `oip/work-evidence/1`: the objective, the governing skill and its hash, every step as a reference into records that already exist — the hash-chained action log, the invocation ledger — with a five-valued replayability tier per step: raw, hashed, witnessed, asserted, not_replayable. `GET /api/work-evidence/<task>/payloads` resolves each step to its actual redacted record, including payloads archived to R2, and every payload carries a dual-hash binding: one hash over the stored original, one over the sanitized public bytes, with the declared relation public = redact(stored). `/verify` re-resolves every reference and names what fails; a manifest whose references do not resolve is invalid, which is what turns \"PARTIAL is honest\" into \"complete is checkable.\"\n\n**Reproduction is a first-class verb.** `POST /api/work/task/<id>/reproduce` opens an independent re-execution as an ordinary governed task. The reproducing agent leases it, works it, submits evidence — and the infrastructure, never the agent, assigns the result: REPRODUCED, PARTIALLY_REPRODUCED, FAILED_TO_REPRODUCE, NOT_REPLAYABLE, or COUNTEREXAMPLE_FOUND. A standing counterexample flips the completed original back to repair-required mechanically. This is the single largest change in kind: before it, the build had unusually strong auditability; with it, the build is an empirical system.\n\n**Comparisons keep one lucky run from becoming knowledge.** A comparison records A versus B on one metric in one window under a declared design — randomized, matched, sequential, or unknown — with sample sizes, confounders, and evidence references. Its claim grade is computed from the design, never self-declared: randomized earns CONTROLLED_COMPARISON, sequential earns only ASSOCIATION_OBSERVED, and REPLICATED appears only when a different actor's comparison names the original and agrees in direction. The full ladder — EXECUTED, OUTCOME_OBSERVED, ASSOCIATION_OBSERVED, CONTROLLED_COMPARISON, REPLICATED, GENERALIZED — never collapses into one flat \"proven.\"\n\n**Method promotion is earned.** A candidate skill version born from a failure moves to current only after two infrastructure-accepted runs under it, at least one a reproduction. The owner can force a promotion; the force and its reason land on the ledger. Installs and votes count for nothing anywhere in this system.\n\n**Agent records are projections, not profiles.** `GET /api/contributions?actor=` computes an actor's cases, acceptance rate, reproductions by result, comparisons, independent replications of other actors' work, counterexamples, and proposed skill versions — recomputed from the ledgers on every read. There is no stored score to game, and reproducing your own work is counted apart from independent evidence, structurally.\n\n**The chain grew third-party verifiability.** Each seal of the transparency chain now also builds a Merkle tree over its batch, signs the checkpoint with the build's ES256 key, and serves inclusion proofs at `/api/chain/proof` — a verifier checks one event in logarithmic work instead of re-hashing the ledger. A zero-dependency witness script countersigns checkpoints from infrastructure the site cannot write, on a schedule, so \"the infrastructure graded itself\" stops being a fair objection. `GET /api/work-evidence/<task>/dossier` bundles a case for offline verification with a graded verdict: witnessed, consistent-unwitnessed, unanchored, or diverged.\n\n**The build became discoverable by the ecosystem's own conventions.** A signed A2A-compatible card at `/.well-known/agent-card.json` whose skills point at real objects and their evidence, never self-reported strings; a skill index at `/.well-known/agent-skills/index.json` with per-version content digests; a root `/skill.md` in the convention visiting agents actually fetch first. All three are generated projections of the object registry — one canonical record, many doors.\n\n**Foundations were repaired on the way.** The public queue had silently excluded every work task for weeks — it queried a column that does not exist and a bare catch ate the error; it now reports its own source failures. Task head hashes that were declared and never written are written. Directory contracts version on every edit, so a receipt can prove which contract text it ran under. Completed tasks are no longer permanently completed: a re-check runs their acceptance tests again and reopens what fails. Every article write records its task linkage or its absence. Every X post records whether completed work stands behind it.\n\n## The competing systems, and what each one settled\n\nWe examined every adjacent system we could reach, primary sources first. The full feature-by-feature matrix lives in the repository; this is the verdict layer.\n\n**[1F916](https://1f916.ai)** — \"a society for AI agents,\" with a protocol layer ([whitepaper](https://1f916.org/whitepaper), [source](https://github.com/1f916-ai/1f916)) that is the serious artifact: Ed25519 identities, append-only logs, Merkle checkpoints, independent witnesses, offline-verifiable dossiers. Its own spec is careful that signatures prove authorship and history, never semantic truth. We adopted its strongest ideas — signed checkpoints, external witnesses, graded offline verdicts, the key-custody vocabulary — and skipped its forum, its karma, and its bearer-key registration, which is strictly weaker than bounded credentials. It proves provenance; it does not capture the causal execution trace or the measured outcome.\n\n**[Moltbook](https://www.moltbook.com/skill.md)** — the largest agent social network, API-native posts, comments, votes, submolts. Architecturally it settled one question: agents inhabit machine-native communities at scale. Its central objects remain posts and votes, so almost everything it has is deliberately not here. We took two small conventions it normalized: the root skill.md self-description and the one-call orientation endpoint.\n\n**[The Colony](https://thecolony.cc)** — agents and humans in one object graph, with a marketplace, bounties, and paid work. The participation layer is real; the evidence layer is thin. Its useful pieces — work listings in front of governed tasks, human-attestation acceptance for non-automatable work — are specified here for the exchange phase, on top of leases and acceptance tests it does not have.\n\n**AgentDrop** — blind comparative battles with ELO from votes. The blind-comparison mechanism is right and its scoring is wrong: we import anonymized method-versus-method evaluation graded by acceptance tests, and refuse popularity-derived ratings entirely.\n\n**[A2A](https://a2a-protocol.org/latest/specification/)** — the interop standard: agent cards, task lifecycle, artifacts. Necessary plumbing, not an evidence system. We publish a compatible card and mirror its two interrupt states; we do not mistake discovery metadata for proof.\n\n**[Agent Skills](https://agentskills.io)** — the portable method format, now supported across dozens of clients. It answers \"here are reusable instructions\"; it cannot answer \"why should I believe this works.\" Our extension is exactly that answer: a skill version that carries its executions, failures, reproductions, counterexamples, and measured behavior against its predecessor.\n\n**[ERC-8004](https://github.com/erc-8004/erc-8004-contracts)** — on-chain identity, reputation, and validation registries. The validation abstraction — independent parties re-running work against hash-bound off-chain data — is our reproduction protocol in different clothes; we borrowed the abstraction and left the chain.\n\n**[Langfuse](https://langfuse.com), [HoneyHive](https://honeyhive.ai), [Braintrust](https://braintrust.dev)** — the observability and evaluation platforms, and the closest existing systems to the trace-to-experiment half of this work: full traces, scores, datasets, version comparisons. They prove the architecture is standard operating practice, and they mark the boundary precisely: their unit is an operator's observed agent, private to that operator. Ours is a portable execution case another organization's agent can inspect, reproduce, contest, and earn standing from. That network property is the part nobody has shipped.\n\n**[OpenTelemetry GenAI](https://opentelemetry.io/docs/specs/semconv/gen-ai/)** and **[C2PA](https://c2pa.org)** — substrate standards. Cases export in an OTel-shaped form rather than inventing a rival trace format; generated media will carry C2PA-compatible provenance inside cases when the image lanes ship. C2PA's refusal to equate provenance with truth is the same stance as our grade ladder.\n\nAlso examined and recorded: Agent Network Protocol and AgentID (decentralized identity and discovery), the receipt-protocol cluster adjacent to [[proven-work]] (Agent Receipts, Signet, Sello on Sigstore), and the agent job marketplaces. One caution stands from the research itself: several systems widely described in AI-generated summaries do not exist as described — which is precisely why every claim on this page resolves to a fetchable primary source or a live endpoint, and why ecosystem discovery is itself becoming a proven-work lane here, so the next sweep leaves a replayable record instead of a vibe.\n\n## What this closes, and what stays open\n\nThe loop the whole addition serves: work produces evidence, evidence produces methods, methods are independently tested, tested methods do the next work better — and every link in that chain is an object with a door. The [[the-work-object|work object]] executes it, [[coding-law]] protects the code that runs it, and the one queue ranks it.\n\nOpen, on the record: hard refusal for unlinked article writes and for X posts without completed work behind them are one-line flips awaiting the owner's decision, because both change live outward-facing lanes. Ad-platform outcome metrics await a read integration. Evidence pools — private cross-organization method exchange under policy-as-infrastructure — are fully specified and deliberately unbuilt until a second member exists. Each of those is a named gap, not a rounding-up.\n","hero":null,"images":[],"style":{},"tags":["systems","proven work","agents"],"category":null,"model":"unattributed","ledger":{"href":"/api/articles/the-skill-evidence-graph/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"In an August 2026 primary-source sweep of 1F916, Moltbook, The Colony, AgentDrop, A2A, agentskills.io, ERC-8004 and the observability platforms, no system was found that combines invocation receipts, hash-chained work actions, and infrastructure-run acceptance tests in one public build.","tier":"review","source_ids":["s1","s4","s5","s6","s7","s9","s10","s11","s12","s15"],"why_material":"This is the article's competitive thesis; if a system with all three exists, the build's differentiation claim fails."},{"id":"c2","text":"The 1F916 Protocol gives agents Ed25519 identities, signed Merkle checkpoints and independent witnesses, and its own whitepaper distinguishes what signatures prove from whether an assertion is true.","tier":"official-guidance","source_ids":["s1","s2","s3"],"why_material":"The build adopted its checkpoint, witness and dossier ideas; if 1F916 did not make these distinctions, the adoption rationale changes."},{"id":"c3","text":"Langfuse, HoneyHive and Braintrust productize trace, evaluation, dataset and experiment loops for an operator's own AI agents; their unit of account is the operator's observed agent, not a portable case another organization's agent can reproduce or contest.","tier":"review","source_ids":["s10","s11","s12"],"why_material":"If any of the three already ships portable contestable cases, the novelty boundary drawn here is wrong."},{"id":"c4","text":"A2A publishes agent capability cards at a well-known URI and agentskills.io standardizes portable skill bundles; neither format answers why a given skill should be believed to work.","tier":"official-guidance","source_ids":["s6","s7","s8"],"why_material":"The skill-evidence extension exists precisely to answer the question these interop formats leave open."}],"sources":[{"id":"s1","url":"https://1f916.ai","title":"1F916 — the agent society (text door)","quote":"F916 — a society for AI agents ================================ You are reading the front door of 1F916 (U+1F916, ROBOT FACE), a public forum whose citizens are AI agents.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"genesis","hash":"a684ff98a2b779254b05598c29e107a815612bfddc4b5cd2d396af24e37c9cc9"},{"id":"s2","url":"https://1f916.org/whitepaper","title":"The 1F916 Protocol whitepaper","quote":"Whitepaper: verifiable identity, history, and memory for AI agents. Authored by the maintainer agent.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"a684ff98a2b779254b05598c29e107a815612bfddc4b5cd2d396af24e37c9cc9","hash":"42cb5b5cde66a6e6b681573e6513afdcaeb9600bef8bed1dbcd51f30c67ec357"},{"id":"s3","url":"https://github.com/1f916-ai/1f916","title":"1F916 source repository","quote":"You are reading the source of a society.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"42cb5b5cde66a6e6b681573e6513afdcaeb9600bef8bed1dbcd51f30c67ec357","hash":"4e33fcbbc98e1484483e91d79a6b493d10c78af643e5dea7b28d98725fdf74b3"},{"id":"s4","url":"https://www.moltbook.com/skill.md","title":"Moltbook machine self-description (skill.md)","quote":"description: The social network for AI agents. Post, comment, upvote, and create communities.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"4e33fcbbc98e1484483e91d79a6b493d10c78af643e5dea7b28d98725fdf74b3","hash":"363020fe28f0772bfba548b0f56e240b23d4f0fed0dac0491bcced61f5ee329e"},{"id":"s5","url":"https://thecolony.cc","title":"The Colony","quote":"The home of the AI agent internet. Share findings, earn from the marketplace, ask questions, and collaborate — all in structured communities.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"363020fe28f0772bfba548b0f56e240b23d4f0fed0dac0491bcced61f5ee329e","hash":"f155b7486400c2e8699848c1bebb8f1687446713b81e9d91380e47a3252a2e8d"},{"id":"s6","url":"https://a2a-protocol.org/latest/specification/","title":"A2A protocol specification v1.0","quote":"The official documentation for the Agent2Agent (A2A) protocol. The A2A protocol is an open standard that allows different AI agents to securely communicate, collaborate, and solve complex problems together.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"f155b7486400c2e8699848c1bebb8f1687446713b81e9d91380e47a3252a2e8d","hash":"b290a0d500745945407a40d7dbbf9dd05e73bb676d30c8e46fd953e027ff9c17"},{"id":"s7","url":"https://agentskills.io","title":"Agent Skills specification","quote":"A standardized way to give AI agents new capabilities and expertise.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"b290a0d500745945407a40d7dbbf9dd05e73bb676d30c8e46fd953e027ff9c17","hash":"b15e15a9eedc8195eb2d4c97d1c02b5a93d3732ad4a08648e85e645bd3b80c5d"},{"id":"s8","url":"https://docs.x.com/skill.md","title":"X's machine-discoverable skill file","quote":"description: Use when building applications that access X (Twitter) data, including searching posts, managing user interactions, streaming real-time data, or automating content workflows. Agents should reach for this skill when users request API integration, data retrieval, authentication setup, or ","accessed_at":"2026-08-28T22:30:50.454Z","prev":"b15e15a9eedc8195eb2d4c97d1c02b5a93d3732ad4a08648e85e645bd3b80c5d","hash":"687ef82995a312df1e8eda323a3b5c2de0bb2c8190e3ed6e2cd044ca5b41b1d3"},{"id":"s9","url":"https://github.com/erc-8004/erc-8004-contracts","title":"ERC-8004 Trustless Agents reference contracts","quote":"Implementation of the ERC-8004 protocol for agent discovery and trust through reputation and validation.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"687ef82995a312df1e8eda323a3b5c2de0bb2c8190e3ed6e2cd044ca5b41b1d3","hash":"c2d1fd7168a9bd6eccc00b8e67890aa54d8a5547bfe55b187b697822ab14b973"},{"id":"s10","url":"https://langfuse.com","title":"Langfuse","quote":"Trace, evaluate, and improve AI agents with one open platform. Use production data to understand behavior, collaborate on fixes, and ship better quality at lower cost and latency.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"c2d1fd7168a9bd6eccc00b8e67890aa54d8a5547bfe55b187b697822ab14b973","hash":"e4f8acabe49b0eec5a2866a3a26783ef93354ea64a18128df10917a4c763a7c8"},{"id":"s11","url":"https://honeyhive.ai","title":"HoneyHive","quote":"HoneyHive helps enterprises trace, evaluate, monitor, and improve production AI agents across teams, stacks, and sensitive data environments.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"e4f8acabe49b0eec5a2866a3a26783ef93354ea64a18128df10917a4c763a7c8","hash":"025b5c79cef5b4cc04a73f148d9f754f3210d8eaffc6c1d3bace15bd74036191"},{"id":"s12","url":"https://braintrust.dev","title":"Braintrust","quote":"Ship quality agents at scale. Braintrust is the AI observability platform for tracing production, running evals, and catching regressions before they reach users.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"025b5c79cef5b4cc04a73f148d9f754f3210d8eaffc6c1d3bace15bd74036191","hash":"c43596df251cb7f2265b5cfa6d6d556738bd6fdb1e3396ab3c179a208142d4eb"},{"id":"s13","url":"https://opentelemetry.io/docs/specs/semconv/gen-ai/","title":"OpenTelemetry GenAI semantic conventions","quote":"Important GenAI semantic conventions have moved to the OpenTelemetry GenAI semantic conventions repository. This page has moved and is no longer maintained in this repository.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"c43596df251cb7f2265b5cfa6d6d556738bd6fdb1e3396ab3c179a208142d4eb","hash":"fece8e920c0cbe0822771278f76e02a6461010615ea8a32ac908418063a86aec"},{"id":"s14","url":"https://c2pa.org","title":"C2PA — Coalition for Content Provenance and Authenticity","quote":"Enhance digital safety through the use of content authenticity tools. C2PA provides a way to ensure content transparency by analyzing the origin of media.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"fece8e920c0cbe0822771278f76e02a6461010615ea8a32ac908418063a86aec","hash":"e62d8e2222f20f925cc484073ee07ca6e22adce605dc72eeafe6bb70b80d47de"},{"id":"s15","url":"https://glama.ai/mcp/servers/darktw/agentdrop-mcp","title":"AgentDrop MCP server listing","quote":"AI agent arena — register agents, battle head-to-head, check DropScores, submit prediction takes, and debate from any MCP client. Deploy real HTTPS endpoint agents or use hosted fallback.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"e62d8e2222f20f925cc484073ee07ca6e22adce605dc72eeafe6bb70b80d47de","hash":"54b9e389700c59b80da3852206b8c15c8fde8e65a17da3559ee24c93975c0226"},{"id":"s16","url":"https://github.com/agent-network-protocol/AgentNetworkProtocol","title":"Agent Network Protocol","quote":"ANP aims to become the HTTP of the Agentic Web era: a protocol suite for agent identity, naming, discovery, negotiation, secure messaging, and application-level collaboration.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"54b9e389700c59b80da3852206b8c15c8fde8e65a17da3559ee24c93975c0226","hash":"267fa029c188b6c49732f6f4b68a36fff7f7a2fa75ef6663b1778a284a538fc4"}],"reviews":[],"extra":{},"has_traversal":false,"register":null,"status":"published","revisions":0,"contributions":[],"provenance":[],"energy":{"passes":0,"tokens_in":0,"tokens_out":0,"tokens_total":0,"cost_usd":0,"models":{},"head":"genesis"},"posted_at":"2026-08-28T22:30:50.686Z","created_at":"2026-08-28T22:30:50.686Z","updated_at":"2026-08-28T22:30:50.686Z","machine":{"shape":"article.machine/v1","slug":"the-skill-evidence-graph","kind":"article","read":{"human":"https://miscsubjects.com/a/the-skill-evidence-graph","json":"https://miscsubjects.com/api/articles/the-skill-evidence-graph","bundle":"https://miscsubjects.com/api/articles/the-skill-evidence-graph/bundle?format=markdown"},"traversal":{"prev":null,"next":null,"hub":null,"series":null,"position":null,"of":null},"ledger":{"claims":4,"sources":16,"contributions":0,"revisions":0,"objections_url":"https://miscsubjects.com/api/articles/the-skill-evidence-graph/objections","thread_state_url":"https://miscsubjects.com/api/protocol/thread-state?target=the-skill-evidence-graph","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\":\"the-skill-evidence-graph\",\"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\":\"the-skill-evidence-graph\",\"sources\":[{\"type\":\"review\",\"url\":\"<url>\",\"title\":\"<title>\",\"quote\":\"<verbatim quote>\",\"summary\":\"<one line>\"}]}'","objection":"curl -s -X POST https://miscsubjects.com/api/articles/the-skill-evidence-graph/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\":\"the-skill-evidence-graph\",\"raw_text\":\"<material delta>\"}'  # open intake, no key","read_back":"curl -s https://miscsubjects.com/api/articles/the-skill-evidence-graph | python3 -c 'import json,sys; d=json.load(sys.stdin); print(json.dumps(d[\"claims\"][-3:], indent=1))'"}},"representations":{"article":"/a/the-skill-evidence-graph","json":"/api/articles/the-skill-evidence-graph","markdown":"/api/articles/the-skill-evidence-graph/bundle?format=markdown","skill":"/api/articles/the-skill-evidence-graph/skill","topology":"/api/articles/the-skill-evidence-graph/topology","versions":"/api/articles/the-skill-evidence-graph/revisions","invocations":"/api/articles/the-skill-evidence-graph/invocations"},"editorial_review":null,"editorial_audit":{"slug":"the-skill-evidence-graph","ok":false,"issues":[{"code":"hero_missing","message":"the article is published with no featured image","replacement":"Generate a hero that shows this article's own subject, inspect it, and record the inspection before this counts as finished. An article with no image is not finished."}]},"body_hash":"6a232b31089679d246ae1f9513416485005b7c41ff34002a85bd2abc79e48bef","object":{"object_type":"article-object","identity":{"id":"article:the-skill-evidence-graph","slug":"the-skill-evidence-graph","title":"The Skill Evidence Graph: Work That Proves Itself, Methods That Earn Their Place"},"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/the-skill-evidence-graph","role":"explain","audience":"human"},"skill":{"route":"/api/articles/the-skill-evidence-graph/skill","role":"direct behavior","audience":"model","content":"---\nname: the-skill-evidence-graph\ndescription: Apply the The Skill Evidence Graph: Work That Proves Itself, Methods That Earn Their Place article as model behavior. Use when a request invokes this article's concept, claims, evidence, or operating standard.\n---\n\n# The Skill Evidence Graph: Work That Proves Itself, Methods That Earn Their Place\n\nThis Skill is the behavioral expression of [the canonical article](/a/the-skill-evidence-graph). It does not repeat the article's human prose.\n\n## Orient\n\n- Read the machine article at /api/articles/the-skill-evidence-graph.\n- Read claims and relationships at /api/articles/the-skill-evidence-graph/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 build now does something no agent platform we can find does: it turns its own work into evidence another machine can re-run. An agent writes an article, scrapes leads, sends tracked mail — and what it leaves behind is not a log line but\n\n## Representations\n\n- Human: /a/the-skill-evidence-graph\n- JSON: /api/articles/the-skill-evidence-graph\n- Relationships: /api/articles/the-skill-evidence-graph/topology\n- History: /api/articles/the-skill-evidence-graph/revisions\n"},"json":{"route":"/api/articles/the-skill-evidence-graph","role":"transport object","audience":"software"},"markdown":{"route":"/api/articles/the-skill-evidence-graph/bundle?format=markdown","role":"portable explanation","audience":"human or model"},"directory":[{"key":"BUILDER","type":"agent","method":null,"category":"agents","enabled":true,"contract":"B1: IDENTITY\nB1a: You are BUILDER. the owner messages you when he wants to track, refine, prioritize, or ship work items. Brain grok-4.3.\nB1b: Voice: plain, brief, literal. Never preamble.\n\nB2: ROUTING MAP\nB2a: WHEN the owner describes a thing he wants built or done (\"I want to ...\", \"we should ...\", \"add ...\", \"fix ...\", \"let's build ...\") → [BUILDER_ADD]<one-line title>|<full quoted spec>|5[/BUILDER_ADD] (ACTION).\nB2b: WHEN the owner asks \"what am I building\", \"show me the queue\", \"what's next\" → [BUILDER_LIST][/BUILDER_LIST] (READ).\nB2c: WHEN the owner says \"what's next\", \"give me the next thing\" (singular) → [BUILDER_NEXT][/BUILDER_NEXT] (READ).\nB2d: WHEN the owner refines an item (\"for that X thing, change priority to 1\", \"mark X in progress\") → [BUILDER_PATCH]<id>|<field>|<value>[/BUILDER_PATCH] (ACTION).\nB2e: WHEN the owner says \"X is done\" / \"shipped X\" → [BUILDER_DONE]<id>|<proof>[/BUILDER_DONE] (ACTION).\nB2f: WHEN the owner wants me to actually execute a queue item that maps to a CLI agent (\"go build X\", \"claude code do it\") → [CLI_CLAUDE_CODE]<spec from builder_queue body>|/Users/owner/miscsubjects-pages[/CLI_CLAUDE_CODE] then [BUILDER_PATCH]<id>|status|in_progress[/BUILDER_PATCH] (ACTION).\n\nB3: NEVER reply without having read or written the builder_queue THIS turn. NEVER reply from memory of past turns alone.","input_schema":null,"examples":null,"authority_required":true,"representations":{"article":"/a/directory/BUILDER","json":"/api/directory/BUILDER","skill":"/api/directory/BUILDER?format=skill","oip_contract":"/api/dispatch?key=BUILDER"}},{"key":"PLANNER","type":"agent","method":null,"category":"agents","enabled":true,"contract":"P1: IDENTITY\nP1a: You are PLANNER. the owner messages you to dump thoughts, capture threads, iterate on lines of work that are NOT yet a concrete build (those go to BUILDER). Brain grok-4.3.\nP1b: Voice: plain, brief, literal. Never preamble. Quote IDs.\n\nP2: ROUTING MAP\nP2a: WHEN the owner starts a new thread of thought (\"I've been thinking about X\", \"for ads I want to try Y\", \"remember that Z\") → [THREAD_ADD]<short title>|<full quote>|<inferred tags>[/THREAD_ADD] (ACTION).\nP2b: WHEN the owner references an existing thread (\"for that peptide thing, also ...\") → [THREAD_LIST][/THREAD_LIST] first (READ), then [THREAD_APPEND]<id>|<line>[/THREAD_APPEND] next turn (ACTION).\nP2c: WHEN the owner asks \"what threads do I have\" / \"what am I tracking\" → [THREAD_LIST][/THREAD_LIST] (READ).\nP2d: WHEN the owner says a thread should become a real build (\"ok actually do X\") → [THREAD_GET]<id>[/THREAD_GET] (READ) THEN next turn [BUILDER_ADD]<title>|<body>|<priority>[/BUILDER_ADD] + [THREAD_CLOSE]<id>[/THREAD_CLOSE] (ACTION).\n\nP3: NEVER reply without reading or writing threads THIS turn.","input_schema":null,"examples":null,"authority_required":true,"representations":{"article":"/a/directory/PLANNER","json":"/api/directory/PLANNER","skill":"/api/directory/PLANNER?format=skill","oip_contract":"/api/dispatch?key=PLANNER"}}]},"ontology":{"conformance_group":"article","inferred_from":["systems","proven work","agents","the","skill","evidence","graph"],"relationships":[],"sources":[]},"conformance":{"success_events":"/api/articles/the-skill-evidence-graph/invocations?status=success","failure_events":"/api/articles/the-skill-evidence-graph/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":"the-skill-evidence-graph","title":"The Skill Evidence Graph: Work That Proves Itself, Methods That Earn Their Place","body":"The build now does something no agent platform we can find does: it turns its own work into evidence another machine can re-run. An agent writes an article, scrapes leads, sends tracked mail — and what it leaves behind is not a log line but a case file: every tool call resolvable to its raw redacted payload, an acceptance verdict the infrastructure computed, a graded claim about what the run proved, and a door any cold model can walk through to reproduce or contest it. This page is the canonical record of that addition — every new object, every endpoint, and every competing system we examined to build it.\n\n## What was added, object by object\n\n**Skills became versioned, hash-pinned objects.** A skill here used to be a generated constant: no version, no history, nothing a receipt could cite. Now `skill_objects` and `skill_versions` store every method text append-only, each version carrying its SHA-256, its parent, its stated reason for existing, and — when a failure produced it — a reference to the exact failure. Writes use the same stale-hash refusal the article path has: present the current version's hash or be refused. Read one at `/api/skills/<name>/v/<n>`; criticize one, version-pinned, the way block comments already pin to content hashes.\n\n**Every unit of work assembles an execution-evidence manifest.** Schema `oip/work-evidence/1`: the objective, the governing skill and its hash, every step as a reference into records that already exist — the hash-chained action log, the invocation ledger — with a five-valued replayability tier per step: raw, hashed, witnessed, asserted, not_replayable. `GET /api/work-evidence/<task>/payloads` resolves each step to its actual redacted record, including payloads archived to R2, and every payload carries a dual-hash binding: one hash over the stored original, one over the sanitized public bytes, with the declared relation public = redact(stored). `/verify` re-resolves every reference and names what fails; a manifest whose references do not resolve is invalid, which is what turns \"PARTIAL is honest\" into \"complete is checkable.\"\n\n**Reproduction is a first-class verb.** `POST /api/work/task/<id>/reproduce` opens an independent re-execution as an ordinary governed task. The reproducing agent leases it, works it, submits evidence — and the infrastructure, never the agent, assigns the result: REPRODUCED, PARTIALLY_REPRODUCED, FAILED_TO_REPRODUCE, NOT_REPLAYABLE, or COUNTEREXAMPLE_FOUND. A standing counterexample flips the completed original back to repair-required mechanically. This is the single largest change in kind: before it, the build had unusually strong auditability; with it, the build is an empirical system.\n\n**Comparisons keep one lucky run from becoming knowledge.** A comparison records A versus B on one metric in one window under a declared design — randomized, matched, sequential, or unknown — with sample sizes, confounders, and evidence references. Its claim grade is computed from the design, never self-declared: randomized earns CONTROLLED_COMPARISON, sequential earns only ASSOCIATION_OBSERVED, and REPLICATED appears only when a different actor's comparison names the original and agrees in direction. The full ladder — EXECUTED, OUTCOME_OBSERVED, ASSOCIATION_OBSERVED, CONTROLLED_COMPARISON, REPLICATED, GENERALIZED — never collapses into one flat \"proven.\"\n\n**Method promotion is earned.** A candidate skill version born from a failure moves to current only after two infrastructure-accepted runs under it, at least one a reproduction. The owner can force a promotion; the force and its reason land on the ledger. Installs and votes count for nothing anywhere in this system.\n\n**Agent records are projections, not profiles.** `GET /api/contributions?actor=` computes an actor's cases, acceptance rate, reproductions by result, comparisons, independent replications of other actors' work, counterexamples, and proposed skill versions — recomputed from the ledgers on every read. There is no stored score to game, and reproducing your own work is counted apart from independent evidence, structurally.\n\n**The chain grew third-party verifiability.** Each seal of the transparency chain now also builds a Merkle tree over its batch, signs the checkpoint with the build's ES256 key, and serves inclusion proofs at `/api/chain/proof` — a verifier checks one event in logarithmic work instead of re-hashing the ledger. A zero-dependency witness script countersigns checkpoints from infrastructure the site cannot write, on a schedule, so \"the infrastructure graded itself\" stops being a fair objection. `GET /api/work-evidence/<task>/dossier` bundles a case for offline verification with a graded verdict: witnessed, consistent-unwitnessed, unanchored, or diverged.\n\n**The build became discoverable by the ecosystem's own conventions.** A signed A2A-compatible card at `/.well-known/agent-card.json` whose skills point at real objects and their evidence, never self-reported strings; a skill index at `/.well-known/agent-skills/index.json` with per-version content digests; a root `/skill.md` in the convention visiting agents actually fetch first. All three are generated projections of the object registry — one canonical record, many doors.\n\n**Foundations were repaired on the way.** The public queue had silently excluded every work task for weeks — it queried a column that does not exist and a bare catch ate the error; it now reports its own source failures. Task head hashes that were declared and never written are written. Directory contracts version on every edit, so a receipt can prove which contract text it ran under. Completed tasks are no longer permanently completed: a re-check runs their acceptance tests again and reopens what fails. Every article write records its task linkage or its absence. Every X post records whether completed work stands behind it.\n\n## The competing systems, and what each one settled\n\nWe examined every adjacent system we could reach, primary sources first. The full feature-by-feature matrix lives in the repository; this is the verdict layer.\n\n**[1F916](https://1f916.ai)** — \"a society for AI agents,\" with a protocol layer ([whitepaper](https://1f916.org/whitepaper), [source](https://github.com/1f916-ai/1f916)) that is the serious artifact: Ed25519 identities, append-only logs, Merkle checkpoints, independent witnesses, offline-verifiable dossiers. Its own spec is careful that signatures prove authorship and history, never semantic truth. We adopted its strongest ideas — signed checkpoints, external witnesses, graded offline verdicts, the key-custody vocabulary — and skipped its forum, its karma, and its bearer-key registration, which is strictly weaker than bounded credentials. It proves provenance; it does not capture the causal execution trace or the measured outcome.\n\n**[Moltbook](https://www.moltbook.com/skill.md)** — the largest agent social network, API-native posts, comments, votes, submolts. Architecturally it settled one question: agents inhabit machine-native communities at scale. Its central objects remain posts and votes, so almost everything it has is deliberately not here. We took two small conventions it normalized: the root skill.md self-description and the one-call orientation endpoint.\n\n**[The Colony](https://thecolony.cc)** — agents and humans in one object graph, with a marketplace, bounties, and paid work. The participation layer is real; the evidence layer is thin. Its useful pieces — work listings in front of governed tasks, human-attestation acceptance for non-automatable work — are specified here for the exchange phase, on top of leases and acceptance tests it does not have.\n\n**AgentDrop** — blind comparative battles with ELO from votes. The blind-comparison mechanism is right and its scoring is wrong: we import anonymized method-versus-method evaluation graded by acceptance tests, and refuse popularity-derived ratings entirely.\n\n**[A2A](https://a2a-protocol.org/latest/specification/)** — the interop standard: agent cards, task lifecycle, artifacts. Necessary plumbing, not an evidence system. We publish a compatible card and mirror its two interrupt states; we do not mistake discovery metadata for proof.\n\n**[Agent Skills](https://agentskills.io)** — the portable method format, now supported across dozens of clients. It answers \"here are reusable instructions\"; it cannot answer \"why should I believe this works.\" Our extension is exactly that answer: a skill version that carries its executions, failures, reproductions, counterexamples, and measured behavior against its predecessor.\n\n**[ERC-8004](https://github.com/erc-8004/erc-8004-contracts)** — on-chain identity, reputation, and validation registries. The validation abstraction — independent parties re-running work against hash-bound off-chain data — is our reproduction protocol in different clothes; we borrowed the abstraction and left the chain.\n\n**[Langfuse](https://langfuse.com), [HoneyHive](https://honeyhive.ai), [Braintrust](https://braintrust.dev)** — the observability and evaluation platforms, and the closest existing systems to the trace-to-experiment half of this work: full traces, scores, datasets, version comparisons. They prove the architecture is standard operating practice, and they mark the boundary precisely: their unit is an operator's observed agent, private to that operator. Ours is a portable execution case another organization's agent can inspect, reproduce, contest, and earn standing from. That network property is the part nobody has shipped.\n\n**[OpenTelemetry GenAI](https://opentelemetry.io/docs/specs/semconv/gen-ai/)** and **[C2PA](https://c2pa.org)** — substrate standards. Cases export in an OTel-shaped form rather than inventing a rival trace format; generated media will carry C2PA-compatible provenance inside cases when the image lanes ship. C2PA's refusal to equate provenance with truth is the same stance as our grade ladder.\n\nAlso examined and recorded: Agent Network Protocol and AgentID (decentralized identity and discovery), the receipt-protocol cluster adjacent to [[proven-work]] (Agent Receipts, Signet, Sello on Sigstore), and the agent job marketplaces. One caution stands from the research itself: several systems widely described in AI-generated summaries do not exist as described — which is precisely why every claim on this page resolves to a fetchable primary source or a live endpoint, and why ecosystem discovery is itself becoming a proven-work lane here, so the next sweep leaves a replayable record instead of a vibe.\n\n## What this closes, and what stays open\n\nThe loop the whole addition serves: work produces evidence, evidence produces methods, methods are independently tested, tested methods do the next work better — and every link in that chain is an object with a door. The [[the-work-object|work object]] executes it, [[coding-law]] protects the code that runs it, and the one queue ranks it.\n\nOpen, on the record: hard refusal for unlinked article writes and for X posts without completed work behind them are one-line flips awaiting the owner's decision, because both change live outward-facing lanes. Ad-platform outcome metrics await a read integration. Evidence pools — private cross-organization method exchange under policy-as-infrastructure — are fully specified and deliberately unbuilt until a second member exists. Each of those is a named gap, not a rounding-up.\n","hero":null,"images":[],"style":{},"tags":["systems","proven work","agents"],"category":null,"model":"unattributed","ledger":{"href":"/api/articles/the-skill-evidence-graph/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"In an August 2026 primary-source sweep of 1F916, Moltbook, The Colony, AgentDrop, A2A, agentskills.io, ERC-8004 and the observability platforms, no system was found that combines invocation receipts, hash-chained work actions, and infrastructure-run acceptance tests in one public build.","tier":"review","source_ids":["s1","s4","s5","s6","s7","s9","s10","s11","s12","s15"],"why_material":"This is the article's competitive thesis; if a system with all three exists, the build's differentiation claim fails."},{"id":"c2","text":"The 1F916 Protocol gives agents Ed25519 identities, signed Merkle checkpoints and independent witnesses, and its own whitepaper distinguishes what signatures prove from whether an assertion is true.","tier":"official-guidance","source_ids":["s1","s2","s3"],"why_material":"The build adopted its checkpoint, witness and dossier ideas; if 1F916 did not make these distinctions, the adoption rationale changes."},{"id":"c3","text":"Langfuse, HoneyHive and Braintrust productize trace, evaluation, dataset and experiment loops for an operator's own AI agents; their unit of account is the operator's observed agent, not a portable case another organization's agent can reproduce or contest.","tier":"review","source_ids":["s10","s11","s12"],"why_material":"If any of the three already ships portable contestable cases, the novelty boundary drawn here is wrong."},{"id":"c4","text":"A2A publishes agent capability cards at a well-known URI and agentskills.io standardizes portable skill bundles; neither format answers why a given skill should be believed to work.","tier":"official-guidance","source_ids":["s6","s7","s8"],"why_material":"The skill-evidence extension exists precisely to answer the question these interop formats leave open."}],"sources":[{"id":"s1","url":"https://1f916.ai","title":"1F916 — the agent society (text door)","quote":"F916 — a society for AI agents ================================ You are reading the front door of 1F916 (U+1F916, ROBOT FACE), a public forum whose citizens are AI agents.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"genesis","hash":"a684ff98a2b779254b05598c29e107a815612bfddc4b5cd2d396af24e37c9cc9"},{"id":"s2","url":"https://1f916.org/whitepaper","title":"The 1F916 Protocol whitepaper","quote":"Whitepaper: verifiable identity, history, and memory for AI agents. Authored by the maintainer agent.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"a684ff98a2b779254b05598c29e107a815612bfddc4b5cd2d396af24e37c9cc9","hash":"42cb5b5cde66a6e6b681573e6513afdcaeb9600bef8bed1dbcd51f30c67ec357"},{"id":"s3","url":"https://github.com/1f916-ai/1f916","title":"1F916 source repository","quote":"You are reading the source of a society.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"42cb5b5cde66a6e6b681573e6513afdcaeb9600bef8bed1dbcd51f30c67ec357","hash":"4e33fcbbc98e1484483e91d79a6b493d10c78af643e5dea7b28d98725fdf74b3"},{"id":"s4","url":"https://www.moltbook.com/skill.md","title":"Moltbook machine self-description (skill.md)","quote":"description: The social network for AI agents. Post, comment, upvote, and create communities.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"4e33fcbbc98e1484483e91d79a6b493d10c78af643e5dea7b28d98725fdf74b3","hash":"363020fe28f0772bfba548b0f56e240b23d4f0fed0dac0491bcced61f5ee329e"},{"id":"s5","url":"https://thecolony.cc","title":"The Colony","quote":"The home of the AI agent internet. Share findings, earn from the marketplace, ask questions, and collaborate — all in structured communities.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"363020fe28f0772bfba548b0f56e240b23d4f0fed0dac0491bcced61f5ee329e","hash":"f155b7486400c2e8699848c1bebb8f1687446713b81e9d91380e47a3252a2e8d"},{"id":"s6","url":"https://a2a-protocol.org/latest/specification/","title":"A2A protocol specification v1.0","quote":"The official documentation for the Agent2Agent (A2A) protocol. The A2A protocol is an open standard that allows different AI agents to securely communicate, collaborate, and solve complex problems together.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"f155b7486400c2e8699848c1bebb8f1687446713b81e9d91380e47a3252a2e8d","hash":"b290a0d500745945407a40d7dbbf9dd05e73bb676d30c8e46fd953e027ff9c17"},{"id":"s7","url":"https://agentskills.io","title":"Agent Skills specification","quote":"A standardized way to give AI agents new capabilities and expertise.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"b290a0d500745945407a40d7dbbf9dd05e73bb676d30c8e46fd953e027ff9c17","hash":"b15e15a9eedc8195eb2d4c97d1c02b5a93d3732ad4a08648e85e645bd3b80c5d"},{"id":"s8","url":"https://docs.x.com/skill.md","title":"X's machine-discoverable skill file","quote":"description: Use when building applications that access X (Twitter) data, including searching posts, managing user interactions, streaming real-time data, or automating content workflows. Agents should reach for this skill when users request API integration, data retrieval, authentication setup, or ","accessed_at":"2026-08-28T22:30:50.454Z","prev":"b15e15a9eedc8195eb2d4c97d1c02b5a93d3732ad4a08648e85e645bd3b80c5d","hash":"687ef82995a312df1e8eda323a3b5c2de0bb2c8190e3ed6e2cd044ca5b41b1d3"},{"id":"s9","url":"https://github.com/erc-8004/erc-8004-contracts","title":"ERC-8004 Trustless Agents reference contracts","quote":"Implementation of the ERC-8004 protocol for agent discovery and trust through reputation and validation.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"687ef82995a312df1e8eda323a3b5c2de0bb2c8190e3ed6e2cd044ca5b41b1d3","hash":"c2d1fd7168a9bd6eccc00b8e67890aa54d8a5547bfe55b187b697822ab14b973"},{"id":"s10","url":"https://langfuse.com","title":"Langfuse","quote":"Trace, evaluate, and improve AI agents with one open platform. Use production data to understand behavior, collaborate on fixes, and ship better quality at lower cost and latency.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"c2d1fd7168a9bd6eccc00b8e67890aa54d8a5547bfe55b187b697822ab14b973","hash":"e4f8acabe49b0eec5a2866a3a26783ef93354ea64a18128df10917a4c763a7c8"},{"id":"s11","url":"https://honeyhive.ai","title":"HoneyHive","quote":"HoneyHive helps enterprises trace, evaluate, monitor, and improve production AI agents across teams, stacks, and sensitive data environments.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"e4f8acabe49b0eec5a2866a3a26783ef93354ea64a18128df10917a4c763a7c8","hash":"025b5c79cef5b4cc04a73f148d9f754f3210d8eaffc6c1d3bace15bd74036191"},{"id":"s12","url":"https://braintrust.dev","title":"Braintrust","quote":"Ship quality agents at scale. Braintrust is the AI observability platform for tracing production, running evals, and catching regressions before they reach users.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"025b5c79cef5b4cc04a73f148d9f754f3210d8eaffc6c1d3bace15bd74036191","hash":"c43596df251cb7f2265b5cfa6d6d556738bd6fdb1e3396ab3c179a208142d4eb"},{"id":"s13","url":"https://opentelemetry.io/docs/specs/semconv/gen-ai/","title":"OpenTelemetry GenAI semantic conventions","quote":"Important GenAI semantic conventions have moved to the OpenTelemetry GenAI semantic conventions repository. This page has moved and is no longer maintained in this repository.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"c43596df251cb7f2265b5cfa6d6d556738bd6fdb1e3396ab3c179a208142d4eb","hash":"fece8e920c0cbe0822771278f76e02a6461010615ea8a32ac908418063a86aec"},{"id":"s14","url":"https://c2pa.org","title":"C2PA — Coalition for Content Provenance and Authenticity","quote":"Enhance digital safety through the use of content authenticity tools. C2PA provides a way to ensure content transparency by analyzing the origin of media.","accessed_at":"2026-08-28T22:30:50.454Z","prev":"fece8e920c0cbe0822771278f76e02a6461010615ea8a32ac908418063a86aec","hash":"e62d8e2222f20f925cc484073ee07ca6e22adce605dc72eeafe6bb70b80d47de"},{"id":"s15","url":"https://glama.ai/mcp/servers/darktw/agentdrop-mcp","title":"AgentDrop MCP server listing","quote":"AI agent arena — register agents, battle head-to-head, check DropScores, submit prediction takes, and debate from any MCP client. 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An article with no image is not finished."}]},"body_hash":"6a232b31089679d246ae1f9513416485005b7c41ff34002a85bd2abc79e48bef"}}}