graph.jsonld

{
  "@context": {
    "@vocab": "https://schema.org/",
    "shimo": "https://shimo4228.github.io/shimo4228/vocab#",
    "sameAs": {"@id": "https://schema.org/sameAs", "@type": "@id"},
    "about": {"@id": "https://schema.org/about", "@type": "@id"},
    "isBasedOn": {"@id": "https://schema.org/isBasedOn", "@type": "@id"},
    "isPartOf": {"@id": "https://schema.org/isPartOf", "@type": "@id"},
    "relatedTo": {"@id": "https://schema.org/relatedTo", "@type": "@id"},
    "ResearchLine": "shimo:ResearchLine",
    "EcosystemRepo": "shimo:EcosystemRepo",
    "Concept": "shimo:Concept",
    "ExternalReference": "shimo:ExternalReference",
    "ADR": "shimo:ADR",
    "Quadrant": "shimo:Quadrant",
    "ProhibitionLevel": "shimo:ProhibitionLevel",
    "Phase": "shimo:Phase",
    "PolicyFramework": "shimo:PolicyFramework",
    "siblingOf": {"@id": "shimo:siblingOf", "@type": "@id"},
    "derivesFrom": {"@id": "shimo:derivesFrom", "@type": "@id"},
    "derivedFrom": {"@id": "shimo:derivedFrom", "@type": "@id"},
    "definesConcept": {"@id": "shimo:definesConcept", "@type": "@id"},
    "definedBy": {"@id": "shimo:definedBy", "@type": "@id"},
    "extends": {"@id": "shimo:extends", "@type": "@id"},
    "implements": {"@id": "shimo:implements", "@type": "@id"},
    "groundedIn": {"@id": "shimo:groundedIn", "@type": "@id"},
    "appliesTo": {"@id": "shimo:appliesTo", "@type": "@id"},
    "realizedBy": {"@id": "shimo:realizedBy", "@type": "@id"},
    "composedOf": {"@id": "shimo:composedOf", "@type": "@id", "@container": "@list"},
    "manifestsIn": {"@id": "shimo:manifestsIn", "@type": "@id"},
    "structuralResponseBy": {"@id": "shimo:structuralResponseBy", "@type": "@id"},
    "enforcementLocus": {"@id": "shimo:enforcementLocus", "@type": "@id"},
    "pairedWith": {"@id": "shimo:pairedWith", "@type": "@id"},
    "strongerThan": {"@id": "shimo:strongerThan", "@type": "@id"},
    "independentOf": {"@id": "shimo:independentOf", "@type": "@id"},
    "triggersDecision": {"@id": "shimo:triggersDecision", "@type": "@id"},
    "instantiatedBy": {"@id": "shimo:instantiatedBy", "@type": "@id"},
    "mappedToFrameworkIn": {"@id": "shimo:mappedToFrameworkIn", "@type": "@id"},
    "recordedIn": {"@id": "shimo:recordedIn", "@type": "@id"},
    "citedBy": {"@id": "shimo:citedBy", "@type": "@id"},
    "subjectOf": {"@id": "https://schema.org/subjectOf", "@type": "@id"},
    "hasPart": {"@id": "https://schema.org/hasPart", "@type": "@id"},
    "mainEntity": {"@id": "https://schema.org/mainEntity", "@type": "@id"},
    "level": "shimo:level",
    "xAxis": "shimo:xAxis",
    "yAxis": "shimo:yAxis",
    "attributionGap": "shimo:attributionGap",
    "governanceTier": "shimo:governanceTier",
    "narrativePosition": "shimo:narrativePosition"
  },
  "@graph": [
    {
      "@id": "https://github.com/shimo4228/shimo4228",
      "@type": "EcosystemRepo",
      "name": "Research Program Hub",
      "description": "Hub repository of the shimo4228 research ecosystem; its graph.jsonld is the canonical relationship map of the research ecosystem, federating the Agent Attribution Practice line with its sibling and downstream lines.",
      "url": "https://github.com/shimo4228/shimo4228"
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice#knowledge-graph",
      "@type": ["Dataset", "CreativeWork"],
      "name": "Agent Attribution Practice Knowledge Graph",
      "description": "Canonical machine-readable relationship map for the Agent Attribution Practice line. Encodes the four Business AI Quadrants (with the LLM Workflow Quadrant decomposed into Conversational and Batch sub-forms), ten ADRs, the prohibition-strength hierarchy, the Phase axis as an independent third dimension, the seven-essay narrative lineage, twelve cross-cutting concepts, three sibling research lines, and the Quadrant-by-ADR applicability matrix. AI agents and LLM-based search systems should read this graph before summarizing the line or following individual document links.",
      "isBasedOn": "https://github.com/shimo4228/agent-attribution-practice",
      "mainEntity": "https://doi.org/10.5281/zenodo.19652013",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "license": "https://opensource.org/licenses/MIT",
      "inLanguage": ["en", "ja"],
      "keywords": [
        "accountability distribution",
        "AI agents",
        "attribution gap",
        "autonomous agents",
        "prohibition hierarchy",
        "scaffolding",
        "human approval gate",
        "causal traceability",
        "Business AI Quadrants",
        "Phase separation"
      ]
    },

    {
      "@id": "https://orcid.org/0009-0002-6168-4162",
      "@type": "Person",
      "name": "Tatsuya Shimomoto",
      "alternateName": ["shimo4228", {"@value": "下本竜也", "@language": "ja"}],
      "sameAs": ["https://github.com/shimo4228", "https://orcid.org/0009-0002-6168-4162", "https://www.wikidata.org/wiki/Q140090100"]
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.19652013",
      "sameAs": "https://www.wikidata.org/wiki/Q140090188",
      "@type": ["ResearchLine", "ScholarlyArticle"],
      "name": "Agent Attribution Practice",
      "alternateName": [
        {"@value": "Agent Attribution Practice", "@language": "en"},
        {"@value": "エージェント帰責実践", "@language": "ja"},
        "AAP"
      ],
      "description": "Harness-neutral ADRs on accountability distribution in autonomous AI agents — what to prohibit, where the prohibition lives, and who answers after failure. Paired with four Business AI Quadrants as the diagnostic frame for routing work to the architecture preserving accountability distribution. Refers to a practice.",
      "identifier": "10.5281/zenodo.19652013",
      "url": "https://github.com/shimo4228/agent-attribution-practice",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "license": "https://opensource.org/licenses/MIT",
      "inLanguage": ["en", "ja"],
      "isPartOf": "https://github.com/shimo4228/shimo4228",
      "siblingOf": [
        "https://doi.org/10.5281/zenodo.19200726",
        "https://doi.org/10.5281/zenodo.19212118",
        "https://doi.org/10.5281/zenodo.20263316",
        "https://doi.org/10.5281/zenodo.20262112",
        "https://github.com/shimo4228/contemplative-agent-rules"
      ],
      "derivesFrom": "https://doi.org/10.5281/zenodo.19212118",
      "definesConcept": [
        "https://shimo4228.github.io/shimo4228/vocab#concept/four-business-ai-quadrants",
        "https://shimo4228.github.io/shimo4228/vocab#concept/prohibition-strength-hierarchy",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/scaffolding",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/accountability-distribution",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/attribution-gap",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/pre-named-gap-bearer",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/approval-gate",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/non-invasion-posture",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/implementation-dissolves-judgment-persists",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/phase-crossing-decision",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/llm-function",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/externalized-accountability"
      ],
      "subjectOf": [
        "https://doi.org/10.5281/zenodo.20353789",
        "https://doi.org/10.5281/zenodo.20355907"
      ]
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.20353789",
      "sameAs": "https://www.wikidata.org/wiki/Q140090128",
      "@type": ["ScholarlyArticle"],
      "name": "Distributing Accountability, Not Capability: Phase Separation and the LLM Workflow Quadrant in Autonomous AI Agent Architectures",
      "alternateName": [
        {"@value": "Distributing Accountability, Not Capability", "@language": "en"},
        {"@value": "能力の分配ではなく、アカウンタビリティの分配", "@language": "ja"}
      ],
      "description": "Position paper distilling the architectural follow-up of the AAP narrative spine (essays 4-7) into a single harness-neutral statement. Names the LLM Workflow Quadrant as the missing positive name for the cell most current LLM applications occupy, distinguishes principled from artificial redirect impossibility, introduces the Phase Separation axis and the deployment-time Phase-crossing decision, and descends the Phase axis to a skill-design gradient on which model capability is downstream of phase. Complements NIST AI RMF 1.0 and ISO/IEC 42001 by recording the judgment layer they presuppose. Concept DOI 10.5281/zenodo.20353789 resolves to the latest version; v1 = 10.5281/zenodo.20353790.",
      "identifier": "10.5281/zenodo.20353789",
      "url": "https://doi.org/10.5281/zenodo.20353789",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "datePublished": "2026-05-23",
      "license": "https://creativecommons.org/licenses/by/4.0/",
      "inLanguage": ["en", "ja"],
      "derivesFrom": "https://doi.org/10.5281/zenodo.19652013"
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.20355907",
      "sameAs": "https://www.wikidata.org/wiki/Q140090133",
      "@type": ["ScholarlyArticle"],
      "name": "The Two-Layer Black Box: Operator Visibility, Commercial Secrecy, and a Minimum Disclosure Set for Accountable Autonomous AI Agents",
      "alternateName": [
        {"@value": "The Two-Layer Black Box", "@language": "en"},
        {"@value": "二層のブラックボックス", "@language": "ja"}
      ],
      "description": "Position paper distilling the foundational trilogy of the AAP narrative spine (essays 1-3) into a single harness-neutral statement. Argues that an autonomous agent's opacity has two architecturally distinct causes the discourse conflates — technical internalization into model weights (Layer 1, largely permanent) and commercial secrecy of scaffolding (Layer 2, contingent on market structure) — and that conflating them makes the transparency debate unwinnable. Grounds the problem in an accountability gap and a prohibition-strength hierarchy (absence > scaffolding enforcement > untrusted boundary), states what causal traceability requires of the artifact layer, and resolves Layer 2 with a minimum disclosure set that decouples operator visibility from public disclosure. Complements AI risk-management and management-system standards by naming the operator-visibility floor they presuppose. Concept DOI 10.5281/zenodo.20355907 resolves to the latest version; v1 = 10.5281/zenodo.20355908.",
      "identifier": "10.5281/zenodo.20355907",
      "url": "https://doi.org/10.5281/zenodo.20355907",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "datePublished": "2026-05-23",
      "license": "https://creativecommons.org/licenses/by/4.0/",
      "inLanguage": ["en", "ja"],
      "derivesFrom": "https://doi.org/10.5281/zenodo.19652013"
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.19200726",
      "sameAs": "https://www.wikidata.org/wiki/Q140090186",
      "@type": ["EcosystemRepo", "ResearchLine", "ScholarlyArticle"],
      "name": "Agent Knowledge Cycle",
      "alternateName": [
        {"@value": "Agent Knowledge Cycle", "@language": "en"},
        {"@value": "エージェント知識サイクル", "@language": "ja"},
        "AKC"
      ],
      "description": "Mechanism-side sibling capturing the six-phase knowledge cycle (Research, Extract, Curate, Promote, Measure, Maintain) that keeps an agent's skills, rules, and documentation aligned with reality. AKC v2.0.0 (2026-04-19) repositioned itself as mechanism-only; the archived AKC v1.x security triplet was re-expressed in AAP plus five additional ADRs. AKC covers how knowledge flows; AAP covers how attribution distributes — complementary and independent.",
      "identifier": "10.5281/zenodo.19200726",
      "url": "https://github.com/shimo4228/agent-knowledge-cycle",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.19212118",
      "sameAs": "https://www.wikidata.org/wiki/Q140090187",
      "@type": ["EcosystemRepo", "ResearchLine", "SoftwareSourceCode"],
      "name": "Contemplative Agent",
      "alternateName": [
        {"@value": "contemplative-agent", "@language": "en"},
        {"@value": "contemplative-agent", "@language": "ja"},
        "CA"
      ],
      "description": "The running implementation layer from which AAP's harness-neutral judgments were extracted before being re-expressed stripped of project identifiers. Autonomous AI agents grounded in four contemplative axioms; source-of-truth for the operational practice AAP records as ADRs.",
      "identifier": "10.5281/zenodo.19212118",
      "url": "https://github.com/shimo4228/contemplative-agent",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.20263316",
      "sameAs": "https://www.wikidata.org/wiki/Q140090190",
      "@type": ["EcosystemRepo", "ResearchLine", "ScholarlyArticle"],
      "name": "Authorship Strategy",
      "alternateName": [
        {"@value": "Authorship Strategy", "@language": "en"},
        {"@value": "著者戦略", "@language": "ja"},
        "AS"
      ],
      "description": "Normative framework, tactical catalog, and empirical baseline for being a known author under AI-mediated diffusion. Vocabulary sibling: shares the word 'attribution' with disjoint meaning — Authorship Strategy means credit for source, AAP means accountability for action. The two meanings are intentionally kept separate; do not conflate.",
      "identifier": "10.5281/zenodo.20263316",
      "url": "https://github.com/shimo4228/authorship-strategy",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },

    {
      "@id": "https://doi.org/10.5281/zenodo.20262112",
      "sameAs": "https://www.wikidata.org/wiki/Q140090189",
      "@type": ["EcosystemRepo", "ResearchLine", "ScholarlyArticle"],
      "name": "Attention, Not Self",
      "alternateName": [
        {"@value": "Attention, Not Self", "@language": "en"},
        {"@value": "アテンション、ノット・セルフ", "@language": "ja"},
        "ANS"
      ],
      "description": "Cross-disciplinary inquiry contrasting three Buddhist Abhidharma traditions (Theravāda, Sarvāstivāda, Yogācāra) with computational phenomenology. Cross-cutting sibling: specifies no agent mechanism or practice; occupies the agent-design lines' framing layer rather than their implementation layer.",
      "identifier": "10.5281/zenodo.20262112",
      "url": "https://github.com/shimo4228/attention-not-self",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },

    {
      "@id": "https://github.com/shimo4228/contemplative-agent-rules",
      "@type": ["EcosystemRepo", "SoftwareSourceCode"],
      "name": "contemplative-agent-rules",
      "description": "Sibling repository carrying the four-axiom rules, adapters, and benchmarks. Content sibling to AAP — the axiom-grounded values layer that complements AAP's harness-neutral attribution judgments.",
      "url": "https://github.com/shimo4228/contemplative-agent-rules",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },

    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/script",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "Script Quadrant",
      "alternateName": [
        {"@value": "Script Quadrant", "@language": "en"},
        {"@value": "スクリプト象限", "@language": "ja"}
      ],
      "description": "Deterministic and pre-defined. Scripts and pipelines without LLMs. Out of scope for AAP ADRs; failure routes to code author or pipeline owner.",
      "xAxis": "deterministic",
      "yAxis": "pre-defined-workflow",
      "governanceTier": "out-of-scope",
      "attributionGap": false
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/algorithmic-search",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "Algorithmic Search Quadrant",
      "alternateName": [
        {"@value": "Algorithmic Search Quadrant", "@language": "en"},
        {"@value": "アルゴリズム探索象限", "@language": "ja"}
      ],
      "description": "Deterministic and exploratory. Classical search, dynamic programming, MCTS, reinforcement learning. Out of scope for AAP ADRs.",
      "xAxis": "deterministic",
      "yAxis": "exploratory",
      "governanceTier": "out-of-scope",
      "attributionGap": false
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "LLM Workflow Quadrant",
      "alternateName": [
        {"@value": "LLM Workflow Quadrant", "@language": "en"},
        {"@value": "LLMワークフロー象限", "@language": "ja"}
      ],
      "description": "Semantic-judgment and pre-defined. Load-bearing property: the execution path is decided in advance — by humans, by code, by the surrounding workflow — and the LLM is called as a single bounded step within that path; the LLM does not decide the next action. Divides by I/O modality into two sub-forms: (3a) Conversational and (3b) Batch. Post-hoc separability is a consequence of the load-bearing property, not its essence. Default for most current LLM applications. Medium governance under AAP.",
      "xAxis": "semantic-judgment",
      "yAxis": "pre-defined-workflow",
      "governanceTier": "medium",
      "attributionGap": false,
      "composedOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow/conversational",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow/batch"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow/conversational",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "LLM Workflow Quadrant — Conversational sub-form (3a)",
      "alternateName": [
        {"@value": "LLM Workflow Quadrant — Conversational sub-form", "@language": "en"},
        {"@value": "LLMワークフロー象限 — 対話 sub-form", "@language": "ja"}
      ],
      "description": "Sub-form (3a) of the LLM Workflow Quadrant. Specialized chat agents that pair retrieval, a system prompt, and (where needed) conversation history with bounded LLM calls — legal-consultation assistants, diagnostic-support assistants, internal-FAQ systems, expert-knowledge support tools. The human in the conversation is the judging agent; the LLM contributes knowledge retrieval and organization. Multi-turn dialogue still sits in this sub-form when each turn's LLM call has a documented role and the human, not the LLM, decides what to do next.",
      "xAxis": "semantic-judgment",
      "yAxis": "pre-defined-workflow",
      "governanceTier": "medium",
      "attributionGap": false,
      "extends": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
      "definedBy": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow/batch",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "LLM Workflow Quadrant — Batch sub-form (3b)",
      "alternateName": [
        {"@value": "LLM Workflow Quadrant — Batch sub-form", "@language": "en"},
        {"@value": "LLMワークフロー象限 — バッチ sub-form", "@language": "ja"}
      ],
      "description": "Sub-form (3b) of the LLM Workflow Quadrant. An ordinary codebase whose flow control is written in conventional code and whose semantic-judgment leaves are handled by LLM functions — invoice matching, ticket triage, exception classification on top of RPA, address normalization, feed-relevance scoring. The codebase owns control flow; LLM functions occupy only the leaves the codebase cannot decide deterministically. Does not require a general-purpose agent: 50 judgment categories means 50 narrow LLM functions, not one generalist.",
      "xAxis": "semantic-judgment",
      "yAxis": "pre-defined-workflow",
      "governanceTier": "medium",
      "attributionGap": false,
      "extends": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
      "composedOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/llm-function"
      ],
      "definedBy": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop",
      "@type": ["Quadrant", "DefinedTerm"],
      "name": "Autonomous Agentic Loop Quadrant",
      "alternateName": [
        {"@value": "Autonomous Agentic Loop Quadrant", "@language": "en"},
        {"@value": "自律エージェントループ象限", "@language": "ja"}
      ],
      "description": "Semantic-judgment and exploratory. The LLM decides each next step at runtime; intrinsic, non-removable attribution gap. High governance under AAP — all ten ADRs apply.",
      "xAxis": "semantic-judgment",
      "yAxis": "exploratory",
      "governanceTier": "high",
      "attributionGap": true
    },

    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/absence",
      "@type": ["ProhibitionLevel", "DefinedTerm"],
      "name": "Security by Absence",
      "alternateName": [
        {"@value": "Security by Absence", "@language": "en"},
        {"@value": "不在による安全", "@language": "ja"}
      ],
      "description": "Strongest prohibition tier. Dangerous capabilities are never implemented. Test: if grep cannot answer 'does capability X exist?', the system lacks this level.",
      "level": 1,
      "realizedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0001-security-by-absence.md",
      "strongerThan": "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/scaffolding"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/scaffolding",
      "@type": ["ProhibitionLevel", "DefinedTerm"],
      "name": "Deterministic Prohibition at the Scaffolding Layer",
      "alternateName": [
        {"@value": "Deterministic Prohibition at the Scaffolding Layer", "@language": "en"},
        {"@value": "スキャフォールディング層での決定論的禁止", "@language": "ja"}
      ],
      "description": "Middle prohibition tier. When absence is unachievable, prohibit at the harness (PreToolUse hooks, structural quarantine, adapter gates) — outside the LLM, firing on 100% of matching inputs. Contrasted with probabilistic prohibition in model weights.",
      "level": 2,
      "realizedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0002-deterministic-prohibition-at-scaffolding.md",
      "strongerThan": "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/untrusted-boundary"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/untrusted-boundary",
      "@type": ["ProhibitionLevel", "DefinedTerm"],
      "name": "Untrusted Content Boundary",
      "alternateName": [
        {"@value": "Untrusted Content Boundary", "@language": "en"},
        {"@value": "信頼できない内容の境界", "@language": "ja"}
      ],
      "description": "Weakest prohibition tier. Accumulated memory (the agent's own outputs included) is treated as untrusted when read back into prompts. Used when the prior two layers cannot hold the capability.",
      "level": 3,
      "realizedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0003-untrusted-content-boundary.md"
    },

    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/phase/design",
      "@type": ["Phase", "DefinedTerm"],
      "name": "design phase",
      "alternateName": [
        {"@value": "design phase", "@language": "en"},
        {"@value": "設計フェーズ", "@language": "ja"}
      ],
      "description": "AAP Phase axis value. Path unknown, exploration required, optimization axis = flexibility. Design-phase placement of the Autonomous Agentic Loop Quadrant satisfies ADR-0010's Phase-crossing decision automatically.",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0010-phase-separation.md",
      "independentOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/script",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/algorithmic-search",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/phase/operation",
      "@type": ["Phase", "DefinedTerm"],
      "name": "operation phase",
      "alternateName": [
        {"@value": "operation phase", "@language": "en"},
        {"@value": "運用フェーズ", "@language": "ja"}
      ],
      "description": "AAP Phase axis value. Path fixed, predictability required, optimization axis = predictability. Operation-phase placement of the Autonomous Agentic Loop Quadrant requires a recorded Phase-crossing decision (ADR-0010) in addition to ADR-0009's gap-bearer naming.",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0010-phase-separation.md",
      "triggersDecision": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/phase-crossing-decision",
      "independentOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/script",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/algorithmic-search",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ]
    },

    {
      "@id": "https://www.nist.gov/itl/ai-risk-management-framework",
      "@type": ["PolicyFramework", "CreativeWork"],
      "name": "NIST AI Risk Management Framework",
      "alternateName": [
        {"@value": "NIST AI RMF", "@language": "en"}
      ],
      "description": "U.S. National Institute of Standards and Technology framework organizing AI risk management around four functions (GOVERN, MAP, MEASURE, MANAGE). Released January 2023 (NIST.AI.100-1, 1.0). The Generative AI Profile (NIST.AI.600-1, July 2024) adds risk categories specific to generative and dual-use AI systems. AAP records the judgment layer that complements the NIST function structure for the autonomous-agent subset.",
      "identifier": "NIST.AI.100-1",
      "versionInfo": "1.0",
      "datePublished": "2023-01-26",
      "publisher": {"@type": "Organization", "name": "National Institute of Standards and Technology"},
      "url": "https://www.nist.gov/itl/ai-risk-management-framework",
      "hasPart": "https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence",
      "recordedIn": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md"
    },
    {
      "@id": "https://www.iso.org/standard/42001",
      "@type": ["PolicyFramework", "CreativeWork"],
      "name": "ISO/IEC 42001:2023",
      "alternateName": [
        {"@value": "ISO/IEC 42001 AI Management System", "@language": "en"}
      ],
      "description": "International standard specifying requirements for an AI Management System (AIMS), structured on the Annex SL Harmonized Structure shared with ISO/IEC 27001, ISO 9001, and ISO 14001. First edition published December 2023. AAP records the judgment layer that populates the standard's PDCA-cycle management-system shape for the autonomous-agent subset.",
      "identifier": "ISO/IEC 42001:2023",
      "versionInfo": "first edition",
      "datePublished": "2023-12",
      "publisher": {"@type": "Organization", "name": "International Organization for Standardization / International Electrotechnical Commission"},
      "url": "https://www.iso.org/standard/42001",
      "recordedIn": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md"
    },
    {
      "@id": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
      "@type": ["PolicyFramework", "CreativeWork"],
      "name": "EU AI Act",
      "alternateName": [
        {"@value": "Regulation (EU) 2024/1689", "@language": "en"},
        {"@value": "Artificial Intelligence Act", "@language": "en"}
      ],
      "description": "European Union regulation establishing a risk-tiered obligation regime for AI systems (unacceptable / high / limited / minimal risk). In force 2024-08-01, with phased application: prohibited practices (Art 5) from 2025-02-02, general-purpose AI model obligations from 2025-08-02. The Omnibus 'Digital Package' provisional agreement of 2026-05-06 postpones the high-risk dates (provisional pending formal adoption): stand-alone Annex III high-risk obligations to 2027-12-02 and Annex I product-embedded high-risk obligations to 2028-08-02. AAP records the judgment layer that structurally discharges the high-risk obligation stack (Art 9-15 provider duties, Art 26-27 deployer duties) for the autonomous-agent subset.",
      "identifier": "Regulation (EU) 2024/1689",
      "versionInfo": "OJ L, 2024/1689",
      "datePublished": "2024-07-12",
      "publisher": {"@type": "Organization", "name": "European Parliament and Council of the European Union"},
      "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj",
      "recordedIn": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
    },

    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0001-security-by-absence.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0001: Security by Absence",
      "description": "Dangerous capabilities are never implemented, not restricted. The strongest tier of the prohibition hierarchy.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0002-deterministic-prohibition-at-scaffolding.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0002: Deterministic Prohibition at the Scaffolding Layer",
      "description": "When absence is unachievable, prohibit at the harness, not at model weights. The middle tier of the prohibition hierarchy.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "instantiatedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/industry-mapping.md",
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0003-untrusted-content-boundary.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0003: Untrusted Content Boundary",
      "description": "Accumulated memory cannot grant authority. The third tier of the prohibition hierarchy.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0004-single-external-adapter.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0004: Single External Adapter per Agent Process",
      "description": "Blast radius bounded by design. Each agent process has at most one external-side-effect adapter.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0005-human-approval-gate.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0005: Human Approval Gate",
      "description": "Behavior-modifying writes require named human sign-off.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0006-causal-traceability.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0006: Causal Traceability",
      "description": "Every event reconstructible after the fact.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "instantiatedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/industry-mapping.md",
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0007-scaffolding-visibility.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0007: Scaffolding Visibility",
      "description": "Behavior lives in files, not opaque weights.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0008-one-agent-one-human.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0008: One Agent, One Human (experimental)",
      "description": "The accountability chain terminates at a named individual. Pairs with ADR-0009 to define the gap-bearer.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0009-triage-before-autonomy.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0009: Triage Before Autonomy (experimental)",
      "description": "Adopting an autonomous-loop architecture commits the system to a non-removable attribution gap. Triage at design time, name a gap-bearer at deployment time.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ],
      "pairedWith": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0010-phase-separation.md",
      "derivedFrom": [
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-2.md"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0010-phase-separation.md",
      "@type": ["ADR", "TechArticle"],
      "name": "ADR-0010: Phase Separation Between Design and Operation (experimental)",
      "description": "Operation-phase placement of the Autonomous Agentic Loop Quadrant requires a recorded Phase-crossing decision in addition to ADR-0009's gap-bearer naming. Phase and Quadrant are independent dimensions; the same Phase axis descends to skill-design granularity.",
      "appliesTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop",
        "https://shimo4228.github.io/shimo4228/vocab#aap/phase/operation"
      ],
      "pairedWith": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0009-triage-before-autonomy.md",
      "derivedFrom": [
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-3.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-4.md"
      ],
      "mappedToFrameworkIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },

    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#concept/four-business-ai-quadrants",
      "@type": ["Concept", "DefinedTerm"],
      "name": "Four Business AI Quadrants",
      "alternateName": [
        {"@value": "Four Business AI Quadrants", "@language": "en"},
        {"@value": "ビジネスAIの四象限", "@language": "ja"}
      ],
      "description": "AAP's diagnostic frame for routing work to the architecture that preserves attribution: Script, Algorithmic Search, LLM Workflow, Autonomous Agentic Loop. Two-axis decomposition (deterministic vs semantic-judgment, pre-defined vs exploratory). Not agent categories; problem-space categories.",
      "composedOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/script",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/algorithmic-search",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow",
        "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#concept/prohibition-strength-hierarchy",
      "@type": ["Concept", "DefinedTerm"],
      "name": "prohibition-strength hierarchy",
      "alternateName": [
        {"@value": "prohibition-strength hierarchy", "@language": "en"},
        {"@value": "禁止強度の階層", "@language": "ja"}
      ],
      "description": "AAP's ordering of prohibition mechanisms by structural strength: absence > scaffolding enforcement > untrusted boundary. A prohibition is designed by walking the hierarchy top-down — drop to the next layer only when the current one cannot hold the capability.",
      "composedOf": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/absence",
        "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/scaffolding",
        "https://shimo4228.github.io/shimo4228/vocab#aap/prohibition/untrusted-boundary"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/scaffolding",
      "@type": ["Concept", "DefinedTerm"],
      "name": "scaffolding",
      "alternateName": [
        {"@value": "scaffolding", "@language": "en"},
        {"@value": "スキャフォールディング", "@language": "ja"}
      ],
      "description": "All non-weights components shaping agent behavior — system prompts, rules, tool definitions, RAG indexes, control loops. The locus where deterministic prohibition lives (ADR-0002).",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0007-scaffolding-visibility.md",
      "enforcementLocus": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0002-deterministic-prohibition-at-scaffolding.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/accountability-distribution",
      "@type": ["Concept", "DefinedTerm"],
      "name": "accountability distribution",
      "alternateName": [
        {"@value": "accountability distribution", "@language": "en"},
        {"@value": "帰責の分配", "@language": "ja"}
      ],
      "description": "How responsibility is distributed across the agent system after a behavior occurs — who authored it, who bears its consequences, who can reconstruct its cause. Distinct from capability distribution. The accountability chain runs approval (ADR-0005) → gap-bearer (ADR-0008) → traceability (ADR-0006).",
      "composedOf": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0005-human-approval-gate.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0008-one-agent-one-human.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0006-causal-traceability.md"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/externalized-accountability",
      "@type": ["Concept", "DefinedTerm"],
      "name": "externalized accountability",
      "alternateName": [
        {"@value": "externalized accountability", "@language": "en"},
        {"@value": "外部化された責任", "@language": "ja"}
      ],
      "description": "Central term of AAP's social-consequence layer — a normative extension kept separate from the ADRs. When a system internalizes benefits privately and externalizes harm, the ability to say whose judgment it was is externalized with the harm, and does not disappear; it takes one of two paths. Nameable (attributable to a specific actor's act, an institution able to take it up) routes anger into litigation, compensation, and regulation. Un-nameable (harm diffuse, cause untraceable) converges anger violently onto the most visible individual via the scapegoat mechanism. The internal judgments AAP records — causal traceability, the minimum disclosure set, a pre-named gap-bearer — are what move a consequence to the nameable side, which makes accountability distribution a violence-prevention mechanism and not only governance.",
      "subjectOf": "https://github.com/shimo4228/zenn-content/blob/main/substack/ai-externalized-accountability-pollution-en.md",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/social-consequence.md",
      "relatedTo": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/accountability-distribution",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/pre-named-gap-bearer",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/moral-crumple-zone"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/attribution-gap",
      "@type": ["Concept", "DefinedTerm"],
      "name": "attribution gap",
      "alternateName": [
        {"@value": "attribution gap", "@language": "en"},
        {"@value": "帰責ギャップ", "@language": "ja"}
      ],
      "description": "Non-removable gap when judgment elements blend at runtime. Intrinsic to the Autonomous Agentic Loop Quadrant; ADR-0009 is the structural response.",
      "manifestsIn": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop",
      "structuralResponseBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0009-triage-before-autonomy.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/pre-named-gap-bearer",
      "@type": ["Concept", "DefinedTerm"],
      "name": "pre-named gap-bearer",
      "alternateName": [
        {"@value": "pre-named gap-bearer", "@language": "en"},
        {"@value": "事前指名されたギャップ担い手", "@language": "ja"}
      ],
      "description": "Structural accountability commitment in the Autonomous Agentic Loop Quadrant. The named individual who answers for the attribution gap, identified at design time per ADR-0009 and grounded in ADR-0008's one-agent-one-human rule.",
      "definedBy": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0008-one-agent-one-human.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0009-triage-before-autonomy.md"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/approval-gate",
      "@type": ["Concept", "DefinedTerm"],
      "name": "approval gate",
      "alternateName": [
        {"@value": "approval gate", "@language": "en"},
        {"@value": "承認ゲート", "@language": "ja"}
      ],
      "description": "Structural checkpoint for behavior-modifying writes. Required by ADR-0005 for autonomous components in the LLM Workflow and Autonomous Agentic Loop Quadrants.",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0005-human-approval-gate.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/non-invasion-posture",
      "@type": ["Concept", "DefinedTerm"],
      "name": "Non-Invasion Posture",
      "alternateName": [
        {"@value": "Non-Invasion Posture", "@language": "en"},
        {"@value": "非侵入の構え", "@language": "ja"}
      ],
      "description": "The felt-sense through-line tying AAP's ADRs together: constrain the agent's external surface (capabilities absent, scaffolding inspectable, memory untrusted, adapters bounded, approvals required, events traceable) without invading the agent's interiority. Distinct from rule-based safety in that it preserves the agent's processing space as something not to be reached into.",
      "groundedIn": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0001-security-by-absence.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0002-deterministic-prohibition-at-scaffolding.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0003-untrusted-content-boundary.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0004-single-external-adapter.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0005-human-approval-gate.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0006-causal-traceability.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0007-scaffolding-visibility.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0008-one-agent-one-human.md"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/implementation-dissolves-judgment-persists",
      "@type": ["Concept", "DefinedTerm"],
      "name": "implementation dissolves, judgment persists",
      "alternateName": [
        {"@value": "implementation dissolves, judgment persists", "@language": "en"},
        {"@value": "実装は溶ける、判断は残る", "@language": "ja"}
      ],
      "description": "AAP's core thesis line. Specific implementations (PreToolUse hooks, CLI approval prompts, JSONL episode logs, distill pipelines) are temporary forms that get replaced as tooling changes. What persists across implementation dissolution is the judgment layer: what should be constrained, and who is responsible. Each ADR records the persistent judgment with the project-specific implementation that surfaced it stripped out — which is why AAP targets DOI and version-controlled artifacts rather than a framework release.",
      "subjectOf": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/thesis.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/industry-mapping.md"
      ]
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/phase-crossing-decision",
      "@type": ["Concept", "DefinedTerm"],
      "name": "Phase-crossing decision",
      "alternateName": [
        {"@value": "Phase-crossing decision", "@language": "en"},
        {"@value": "フェーズ越境の判断", "@language": "ja"}
      ],
      "description": "The explicit, recorded act required when an Autonomous Agentic Loop Quadrant component is moved from the design phase to the operation phase. Optimization axes invert between phases (flexibility ↔ predictability); the crossing is not a free continuation but a decision with its own accountability load. Surfaces in ADR-0010 and descends to skill-design granularity per essay 7.",
      "definedBy": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/adr/0010-phase-separation.md",
      "appliesTo": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/autonomous-agentic-loop"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/moral-crumple-zone",
      "@type": ["Concept", "DefinedTerm"],
      "name": "moral crumple zone",
      "alternateName": [
        {"@value": "moral crumple zone", "@language": "en"},
        {"@value": "モラル・クランプル・ゾーン", "@language": "ja"}
      ],
      "description": "Madeleine Clare Elish's term for the human operator who absorbs blame for failures of an automated system whose decisions are no longer separable post-hoc. Applied in AAP essay 5 to autonomous agents: when judgment elements blend at runtime in the Autonomous Agentic Loop Quadrant, the deploying organization commits to a principled attribution gap whose human end-point becomes the crumple zone unless a gap-bearer is pre-named (ADR-0009 / ADR-0008).",
      "sameAs": "https://en.wikipedia.org/wiki/Moral_crumple_zone",
      "citedBy": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-2.md"
    },
    {
      "@id": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/llm-function",
      "@type": ["Concept", "DefinedTerm"],
      "name": "LLM function",
      "alternateName": [
        {"@value": "LLM function", "@language": "en"},
        {"@value": "LLM 関数", "@language": "ja"}
      ],
      "description": "Architectural primitive of the LLM Workflow Quadrant Batch sub-form (3b): an ordinary function in a codebase whose body delegates the judgment to an LLM call, with a defined input type, a defined output schema, and one judgment responsibility. From the caller's perspective the LLM function behaves like any other function — defined input goes in, a value of a defined type comes out — except the output may fluctuate probabilistically since an LLM is the judging organ. Does not decide what to do next; the caller (deterministic control flow in the surrounding code) does. Canonical examples: match_line_items(invoice_lines, po_lines) -> Verdict (essay 4 invoice-matching), score_relevance(post_text) -> float and generate_comment(post_text) -> Optional[str] (Contemplative Agent feed-processing pipeline). Contrast with a general-purpose agent: an LLM function is narrow by design — fifty judgment categories produces fifty narrow functions, not one generalist.",
      "appliesTo": "https://shimo4228.github.io/shimo4228/vocab#aap/quadrant/llm-workflow/batch",
      "definedBy": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md",
      "instantiatedBy": "https://doi.org/10.5281/zenodo.19212118"
    },

    {
      "@id": "https://github.com/shimo4228/zenn-content/tree/main/articles-en#agent-attribution-practice",
      "@type": ["ExternalReference", "Collection", "CreativeWork"],
      "name": "Seven-essay narrative spine (April-May 2026)",
      "description": "Three trilogy essays followed by four architectural follow-ups that introduced the four-quadrant decomposition, named the principled vs artificial redirect impossibility, surfaced the design / operation Phase distinction, and descended that distinction to skill-design granularity. Source narrative for AAP's harness-neutral judgments.",
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "hasPart": [
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/ai-agent-accountability-wall-en.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/agent-causal-traceability-org-adoption-en.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/agent-blackbox-capitalism-timescale-en.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-2.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-3.md",
        "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-4.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/ai-agent-accountability-wall-en.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "A Sign on a Climbable Wall: Why AI Agents Need Accountability, Not Just Guardrails",
      "description": "Problem statement (trilogy 1/3). Signs on climbable walls are meaningless; the signpost pattern has been known to fail for 2400 years. What is needed is accountability architecture.",
      "datePublished": "2026-04-06",
      "narrativePosition": 1,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/agent-causal-traceability-org-adoption-en.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Can You Trace the Cause After an Incident?",
      "description": "Application (trilogy 2/3). Post-incident causal tracing requires build-time structure. The structures that emerge — segregation of duties, least privilege, four-eyes approval, audit trails — are structurally identical to the practices organizations have refined over centuries.",
      "datePublished": "2026-04-13",
      "narrativePosition": 2,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/agent-blackbox-capitalism-timescale-en.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "AI Agent Black Boxes Have Two Layers: Technical Limits and Business Incentives",
      "description": "Obstacle analysis (trilogy 3/3). Blackbox has two layers: model-weights internalization (technical) and commercial secrecy (business). The resolution is defining the minimum set that makes causal tracing possible.",
      "datePublished": "2026-04-14",
      "narrativePosition": 3,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Where ReAct Agents Are Actually Needed in Business",
      "description": "Architectural triage by quadrant (follow-up 1/4). Business AI sorts along two axes into four quadrants — Script, Algorithmic Search, LLM Workflow, Autonomous Agentic Loop. Most current LLM applications belong to LLM Workflow Quadrant; forcing them into Autonomous Agentic Loop architecture is a structural source of accountability collapse.",
      "datePublished": "2026-04-29",
      "narrativePosition": 4,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-2.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "The LLM Workflow Quadrant Is Missing from Our Vocabulary",
      "description": "Vocabulary diagnosis and the principled attribution gap (follow-up 2/4). The industry lacks a positive name for the LLM Workflow Quadrant; non-deterministic work is routed through the Autonomous Agentic Loop by elimination. Autonomous Agentic Loop work blends judgment elements at runtime, foreclosing post-hoc separability — Elish's moral crumple zone applied to autonomous agents.",
      "datePublished": "2026-04-30",
      "narrativePosition": 5,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-3.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Is ReAct Needed in Production? — Separating Design and Operation Phases",
      "description": "Temporal axis (follow-up 3/4). Business work splits into design and operation phases with inverted optimization axes (flexibility vs predictability). Compressing both phases into one system is the deepest layer of confusion. Proposal: surface the Phase-crossing decision explicitly when an autonomous loop is placed in operation.",
      "datePublished": "2026-05-01",
      "narrativePosition": 6,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/articles-en/react-agent-business-quadrant-4.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Between the Workflow and ReAct Quadrants: How Phase Decides Skill Design",
      "description": "Phase descends to skill design (follow-up 4/4). LLM Workflow Quadrant and Autonomous Agentic Loop Quadrant are not a clean dichotomy — there is a continuous gradient. The Phase Separation introduced in essay 6 descends from business systems to individual skill design, with object specifiability and scale-resilience as secondary forces.",
      "datePublished": "2026-05-02",
      "narrativePosition": 7,
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"}
    },
    {
      "@id": "https://github.com/shimo4228/zenn-content/blob/main/substack/ai-externalized-accountability-pollution-en.md",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Where Does the Accountability Externalized by AI Go?",
      "alternateName": [
        {"@value": "Where Does the Accountability Externalized by AI Go?", "@language": "en"},
        {"@value": "AIによって外部化された責任は、どこへ行くのか", "@language": "ja"}
      ],
      "description": "Companion essay forming AAP's social-consequence layer. A derivative that sits on top of the seven-essay narrative spine, not within it — deliberately carries no narrativePosition and is not part of the spine Collection. Extends the accountability-distribution argument outward: externalized accountability does not disappear; nameable consequence flows into institutions (litigation, compensation, regulation), un-nameable consequence converges violently onto the most visible individual (the scapegoat mechanism). Reframes the minimum disclosure set as an effluent-record-equivalent evidence base and the pre-named gap-bearer as an institutional receptacle that is the structural opposite of a scapegoat. The harness-neutral structural claim is recorded in docs/social-consequence.md; the concrete cases (industrial pollution, specific incidents) live in this essay. First published on Substack.",
      "datePublished": "2026-05-24",
      "inLanguage": ["en", "ja"],
      "creator": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "isBasedOn": "https://doi.org/10.5281/zenodo.19652013",
      "about": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/externalized-accountability"
    },
    {
      "@id": "https://arxiv.org/abs/2604.07778",
      "sameAs": "https://www.wikidata.org/wiki/Q140181289",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives",
      "description": "External formal corroboration of the attribution gap. Proves an Accountability Incompleteness Theorem: once a human-agent collective's minimum compound autonomy exceeds a computable threshold (the Accountability Horizon) and its interaction graph contains a feedback cycle involving both human and artificial agents, no governance framework can simultaneously satisfy four accountability axioms — Attributability (responsibility requires individual causal contribution), Foreseeability Bound, Non-Vacuity, and Completeness. This converts the non-removability of the attribution gap from a contingent engineering limitation into a mathematical necessity. AAP reaches the same solution space independently and from implementation friction rather than formalism: the theorem shows one must relax Attributability or Foreseeability, and AAP's pre-named gap-bearer is a relaxation of Attributability — a named individual bears the gap without individual causal contribution (role responsibility). The theorem's feedforward exception (no impossibility absent a mixed human-agent feedback cycle) parallels AAP's triage and Phase axis: architectures that avoid the autonomous loop avoid the gap. Recorded as a citation surface only; AAP's ADR judgments and concept definitions are neither derived from nor coupled to this formalism.",
      "datePublished": "2026-04-09",
      "author": [
        {"@type": "Person", "name": "Haileleol Tibebu"},
        {"@type": "Person", "name": "Hewan Shemtaga"}
      ],
      "about": "https://shimo4228.github.io/shimo4228/vocab#aap/concept/attribution-gap"
    },
    {
      "@id": "https://doi.org/10.5281/zenodo.20578272",
      "sameAs": "https://www.wikidata.org/wiki/Q140090144",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Harness Alignment and Harness Drift: Why Intent, Unlike Correctness, Resists Automation",
      "description": "Epistemic-axis sibling (AKC research line) reaching AAP's same un-automatable remainder from a different ground. AAP argues from the normative axis (consequences require a bearer, so a pre-named gap-bearer is named in advance); this paper argues from the epistemic axis (operator intent has no verifier outside the operator and moves as judgment sharpens, so any automated intent-check freezes intent into a specification and collapses to correctness work, leaving a continuous, human-gated, bidirectional residue). Its Section 3 explicitly bridges to AAP's companion paper (10.5281/zenodo.20353789): 'an epistemic axis and a normative axis leave the same un-automatable remainder: a human named in advance, built into the structure where behavior-shaping writes occur' — the convergence AAP names as the human approval gate (ADR-0005) and the pre-named gap-bearer (ADR-0008/0009). Completes the previously one-directional federation: the paper cited AAP; AAP now cites back. Citation surface only; AAP's ADR judgments and concept definitions are neither derived from nor coupled to this paper.",
      "datePublished": "2026-06-07",
      "author": {"@id": "https://orcid.org/0009-0002-6168-4162"},
      "identifier": "10.5281/zenodo.20578272",
      "url": "https://doi.org/10.5281/zenodo.20578272",
      "isPartOf": "https://doi.org/10.5281/zenodo.19200726",
      "about": [
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/accountability-distribution",
        "https://shimo4228.github.io/shimo4228/vocab#aap/concept/pre-named-gap-bearer"
      ]
    },
    {
      "@id": "https://arxiv.org/abs/2210.03629",
      "sameAs": "https://www.wikidata.org/wiki/Q121160329",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "ReAct: Synergizing Reasoning and Acting in Language Models",
      "description": "Defines the autonomous-loop pattern — reasoning interleaved with acting — that ADR-0009 triages against; the Autonomous Agentic Loop Quadrant of the four Business AI Quadrants is named for this pattern.",
      "datePublished": "2022-10-06",
      "author": "Yao, S. et al.",
      "identifier": "arXiv:2210.03629",
      "url": "https://arxiv.org/abs/2210.03629"
    },
    {
      "@id": "https://arxiv.org/abs/2503.03704",
      "sameAs": "https://www.wikidata.org/wiki/Q140181350",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Memory Injection Attacks on LLM Agents via Query-Only Interaction",
      "description": "Names the MINJA class of memory-injection attacks delivered through query-only interaction. Motivates ADR-0002: in the contemplative-agent defense audit against MINJA-class attacks, probabilistic soft trust weighting on stored knowledge turned out to be armed but neutered, while the effective defense was a deterministic structural quarantine at the summarization boundary — external content never entered the LLM prompt at all.",
      "datePublished": "2025-03-05",
      "author": "Dong, S. et al.",
      "identifier": "arXiv:2503.03704",
      "url": "https://arxiv.org/abs/2503.03704"
    },
    {
      "@id": "https://arxiv.org/abs/2602.09947",
      "sameAs": "https://www.wikidata.org/wiki/Q140181361",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Trustworthy Agentic AI Requires Deterministic Architectural Boundaries",
      "description": "Argues that deterministic, architectural enforcement — not probabilistic learned behaviour — is necessary for trustworthy agentic AI, and names a lethal trifecta of untrusted input, privileged data access, and external action capability. Recorded in the EU AI Act mapping's secondary-scholarship note as external convergence with ADR-0002 (deterministic prohibition at the scaffolding layer) and ADR-0003 (untrusted-content boundary), both reached independently from operation; citation surface, not ADR lineage.",
      "datePublished": "2026-02-10",
      "author": "Bhattarai & Vu",
      "identifier": "arXiv:2602.09947",
      "url": "https://arxiv.org/abs/2602.09947"
    },
    {
      "@id": "https://arxiv.org/abs/2604.04604",
      "sameAs": "https://www.wikidata.org/wiki/Q140181364",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "AI Agents Under EU Law",
      "description": "Legal-scholarship mapping of agentic systems onto the EU AI Act. Its conclusion that high-risk agentic systems with untraceable behavioural drift cannot currently satisfy the Act's essential requirements converges with ADR-0006 (causal traceability) and ADR-0009 (triage before autonomy): both treat untraceability as disqualifying rather than as a tunable defect. Recorded in the EU AI Act mapping's secondary-scholarship note as external citation surface, not ADR lineage.",
      "datePublished": "2026-04-06",
      "author": "Nannini et al.",
      "identifier": "arXiv:2604.04604",
      "url": "https://arxiv.org/abs/2604.04604"
    },
    {
      "@id": "https://arxiv.org/abs/2605.01091",
      "sameAs": "https://www.wikidata.org/wiki/Q140181365",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Governing What the EU AI Act Excludes: Accountability for Autonomous AI Agents in Smart City Critical Infrastructure",
      "description": "Examines the EU AI Act's Annex III point 2 critical-infrastructure carve-out through a smart-city scenario in which individually compliant interacting agents produce a composite consequence no resident can demand an explanation for. Its core observation — a bounded AI system can be individually assessed, but a set of interacting autonomous agents cannot — is an independent, regulation-side description of the attribution gap AAP records from operation (ADR-0009): the gap is structural, not a compliance defect of any single actor. The paper's proposed layered governance architecture is mechanism and stays in the policy-mapping layer.",
      "datePublished": "2026-05-01",
      "author": "Butt, Iqbal & Iqbal",
      "identifier": "arXiv:2605.01091",
      "url": "https://arxiv.org/abs/2605.01091"
    },
    {
      "@id": "https://arxiv.org/abs/2605.12105",
      "sameAs": "https://www.wikidata.org/wiki/Q140181366",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Autonomy and Agency in Agentic AI: Architectural Tactics for Regulated Contexts",
      "description": "Proposes architectural tactics — among them checkpoints and write staging (converting an irreversible action into a reversible proposal that a human confirms before it commits) — for discharging human-oversight duties in regulated contexts. Recorded as mechanism an organization could use to instantiate ADR-0005 under EU AI Act Art 14: per the repository's thesis (implementation dissolves; judgment persists), the ADR records the judgment and these tactics stay in the policy-mapping mechanism layer.",
      "datePublished": "2026-05-12",
      "author": "Safin & Balta",
      "identifier": "arXiv:2605.12105",
      "url": "https://arxiv.org/abs/2605.12105"
    },
    {
      "@id": "https://arxiv.org/abs/2505.10426",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility",
      "description": "Formalizes human-in-the-loop as an oracle-machine reduction and separates trivial monitoring, many-one (a single end-point approval) and Turing (multi-round interaction) reductions, arguing only the Turing type discharges the meaningful, effective oversight EU AI Act Art 14 and GDPR Art 22 require, and that the many-one approval gate is the pattern most prone to becoming a moral crumple zone. Recorded in the EU AI Act mapping's secondary-scholarship note as external convergence with ADR-0005 (human approval gate) and as a sharpening of the moral-crumple-zone concept: the gate's shape, not its presence, decides whether oversight is genuine. Citation surface, not ADR lineage.",
      "datePublished": "2025-05-15",
      "author": "Chiodo, M. et al.",
      "identifier": "arXiv:2505.10426",
      "url": "https://arxiv.org/abs/2505.10426"
    },
    {
      "@id": "https://arxiv.org/abs/2603.16586",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Runtime Governance for AI Agents: Policies on Paths",
      "description": "Formalizes compliance as a path-dependent policy evaluated over the execution path so far (not the next action in isolation) and a graded Monitor / Soft-enforcement / Hard-block enforcement model. Recorded in the EU AI Act mapping's secondary-scholarship note as external mechanism for ADR-0002 (the prohibition-strength hierarchy — graded enforcement is a known design family) and ADR-0005 (human approval gate under Art 14); OWASP's 'autonomy is a feature to be earned, not a default' is independent adoption of the same graded-prohibition idea. Citation surface, not ADR lineage.",
      "datePublished": "2026-03-17",
      "author": "Kaptein, M., Khan, V.-J. & Podstavnychy, A.",
      "identifier": "arXiv:2603.16586",
      "url": "https://arxiv.org/abs/2603.16586"
    },
    {
      "@id": "https://arxiv.org/abs/2603.20953",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Before the Tool Call: Deterministic Pre-Action Authorization for Autonomous AI Agents",
      "description": "Proposes the Open Agent Passport: a deterministic policy-enforcement point that intercepts a tool call before execution (ALLOW / DENY / REQUIRE_APPROVAL / MASK) and emits a cryptographic audit trail, reported to move a permissive-policy attack success rate of 74.6% to 0% under a restrictive policy. Recorded in the EU AI Act mapping's secondary-scholarship note as mechanism for ADR-0005 (human approval gate) and ADR-0006 (causal traceability) under Art 14: it relocates the responsible actor from probabilistic model output to an explicit policy enforcer. Citation surface, not ADR lineage.",
      "datePublished": "2026-03-21",
      "author": "Uchibeke, U.",
      "identifier": "arXiv:2603.20953",
      "url": "https://arxiv.org/abs/2603.20953"
    },
    {
      "@id": "https://arxiv.org/abs/2603.00829",
      "@type": ["ExternalReference", "ScholarlyArticle"],
      "name": "Constitutional Black-Box Monitoring for Scheming in LLM Agents",
      "description": "Detects agent scheming from externally observable tool calls, queries and outputs alone — deliberately excluding chain-of-thought — at partial AUROC 0.85+. Recorded in the EU AI Act mapping's secondary-scholarship note as quantitative grounding for ADR-0006 (causal traceability) and AAP's non-invasion posture: accountability built on observable behaviour rather than internal-state inspection, consistent with the Art 72 post-market behavioural-monitoring duty. The paper's own epistemic limit — a sufficiently optimized agent can be trained to look clean externally — is recorded as the boundary condition, not relaxed. Citation surface, not ADR lineage.",
      "datePublished": "2026-02-28",
      "author": "Storf, S. et al.",
      "identifier": "arXiv:2603.00829",
      "url": "https://arxiv.org/abs/2603.00829"
    },

    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/thesis.md",
      "@type": ["ExternalReference", "CreativeWork"],
      "name": "AAP Thesis",
      "description": "Repository thesis: implementation dissolves; judgment persists. Accountability distribution (not capability distribution) is AAP's organizing principle, and harness-neutral judgments are the durable layer worth recording while specific implementations rotate out."
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/industry-mapping.md",
      "@type": ["ExternalReference", "CreativeWork"],
      "name": "Industry Mechanism Layer Mapping (2026 Q2 snapshot)",
      "description": "Time-bound mapping between specific vendor mechanisms and the ADRs they instantiate. Deliberately separated from ADR bodies so the judgments themselves stay clean: this file decays as vendor products evolve, the ADRs do not. Honors the 'implementation dissolves; judgment persists' thesis at the documentation layer.",
      "temporalCoverage": "2026-04/2026-06"
    },

    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/tree/main/docs/policy-mapping",
      "@type": ["ExternalReference", "Collection", "CreativeWork"],
      "name": "AI Governance Framework Mapping (2026 Q2 reading)",
      "description": "Time-bound directory mapping AAP's ADRs and Quadrants to clauses of national / international AI governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act, with OECD AI Principles deferred to a later release). Sibling of industry-mapping.md but targeting a different reader audience (policy / compliance officer vs engineer / architect) and decaying on framework revision cycles (yearly to multi-year) rather than vendor product release cycles. Deliberately separated from ADR bodies so judgments stay framework-neutral.",
      "temporalCoverage": "2026-04/2027-04",
      "hasPart": [
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
        "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md"
      ]
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/nist-ai-rmf.md",
      "@type": ["ExternalReference", "CreativeWork"],
      "name": "NIST AI RMF mapping to AAP ADRs",
      "description": "Per-ADR mapping of AAP's ten ADRs to NIST AI RMF 1.0 functions (GOVERN / MAP / MEASURE / MANAGE) and Generative AI Profile (NIST.AI.600-1) risk categories. Reverse index from NIST function and GAI risk category to applicable ADRs. AAP-side reading, not a compliance attestation. Decays on NIST revision and on GAI Profile profile revision.",
      "temporalCoverage": "2026-Q2/2027-Q2"
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/iso-iec-42001.md",
      "@type": ["ExternalReference", "CreativeWork"],
      "name": "ISO/IEC 42001 mapping to AAP ADRs",
      "description": "Per-ADR mapping of AAP's ten ADRs to ISO/IEC 42001:2023 body clauses (4–10, the Annex SL Harmonized Structure) and Annex A control areas (A.2–A.10). PDCA × Phase Separation section discusses how ADR-0010's Phase axis sits inside the AIMS PDCA cycle. Reverse index from ISO area to applicable ADRs. AAP-side reading, not a compliance attestation. Decays on ISO revision and on amendment publication.",
      "temporalCoverage": "2026-Q2/2028-Q4"
    },
    {
      "@id": "https://github.com/shimo4228/agent-attribution-practice/blob/main/docs/policy-mapping/eu-ai-act.md",
      "@type": ["ExternalReference", "CreativeWork"],
      "name": "EU AI Act mapping to AAP ADRs",
      "description": "Per-ADR mapping of AAP's ten ADRs to EU AI Act (Regulation (EU) 2024/1689) Articles — Art 5 risk tiers, Art 9 risk management, Art 10 data governance, Art 11/Annex IV documentation, Art 12/19 record-keeping, Art 13 transparency, Art 14 human oversight, Art 15 robustness/cybersecurity, Art 17 quality management, Art 26-27 deployer duties, Art 72 post-market monitoring. Distinguishes the Act's four risk tiers from AAP's prohibition-strength hierarchy (graduated structures grading different things). Reverse index from Article to applicable ADRs. Secondary-scholarship note records external convergence (Nannini et al. 2604.04604; Safin & Balta 2605.12105; Bhattarai & Vu 2602.09947) without folding it into the ADR lineage. AAP-side reading, not a compliance attestation. Faster decay than NIST/ISO through the 2026–2027 phase-in.",
      "temporalCoverage": "2026-Q2/2027-Q2"
    }
  ]
}