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@@ -83,6 +83,9 @@
 {"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/geo","sameAs":"https://www.wikidata.org/wiki/Q131161430","@type":["ExternalReference","ScholarlyArticle"],"name":"GEO: Generative Engine Optimization","author":"Aggarwal, P. et al.","datePublished":"2023","identifier":"arXiv:2311.09735","url":"https://arxiv.org/abs/2311.09735","description":"Measurement framework behind the geo-writer snapshot in ADR-0010 — the first Measure-phase self-application to AKC's own documentation. The README is scored before and after the cognitive-economy change on GEO-derived checks (entity density, question-heading prominence, chunk self-containment, definition density), with both snapshots retained in version control so successive ADRs can track the README's GEO trajectory over time.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0010-human-cognitive-resource-as-central-constraint.md"}
 {"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/intrinsic-metacognitive-learning","sameAs":"https://www.wikidata.org/wiki/Q140181243","@type":["ExternalReference","ScholarlyArticle"],"name":"Truly Self-Improving Agents Require Intrinsic Metacognitive Learning","author":"Liu & van der Schaar","datePublished":"2025","identifier":"arXiv:2506.05109","url":"https://arxiv.org/abs/2506.05109","description":"Taxonomy named in ADR-0005's defense of the human approval gate. In its intrinsic/extrinsic distinction, AKC's gate is extrinsic metacognition — a human-designed loop with a human evaluator at the decision point — and stays so by design, not by immaturity: behavior-modifying writes remain gated because they are where the operator's evolving intent enters the loop.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0005-human-approval-gate.md"}
 {"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/externalization-review","sameAs":"https://www.wikidata.org/wiki/Q140181274","@type":["ExternalReference","ScholarlyArticle"],"name":"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","author":"Zhou et al.","datePublished":"2026","identifier":"arXiv:2604.08224","url":"https://arxiv.org/abs/2604.08224","description":"Field map named in ADR-0013's Related-Work positioning. Frames the field as three coupled forms of externalization — memory, skills, protocols — coordinated by harness engineering as the unification layer; AKC accepts that it sits squarely inside this frame, overlapping the memory and skills quadrants, and locates its delta in loop ownership rather than in the externalization operations themselves.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0013-positioning-within-agent-memory-literature.md"}
+{"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/skillops","sameAs":"https://www.wikidata.org/wiki/Q140352501","@type":["ExternalReference","ScholarlyArticle"],"name":"SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems","author":"Pu, Song & Zhao","datePublished":"2026","identifier":"arXiv:2605.13716","url":"https://arxiv.org/abs/2605.13716","description":"Prior art named in ADR-0013's 2026-06-25 addendum. Frames 'skill technical debt' and a four-dimension library-health diagnosis (utility, compatibility, risk, validation), and proposes a self-maintaining skill ecosystem that prunes, validates, and de-duplicates skills autonomously — the Curate and Maintain operations run without a human in the write path. AKC concedes the maintenance operations as precedent and locates its delta in the structural human approval gate (ADR-0005): SkillOps's defining adjective is self-maintaining, where AKC's Curate and Promote require named human sign-off.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0013-positioning-within-agent-memory-literature.md"}
+{"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/skill-lifecycle-sok","sameAs":"https://www.wikidata.org/wiki/Q140352503","@type":["ExternalReference","ScholarlyArticle"],"name":"SoK: Agentic Skills — Beyond Tool Use in LLM Agents","author":"Jiang et al.","datePublished":"2026","identifier":"arXiv:2602.20867","url":"https://arxiv.org/abs/2602.20867","description":"Field map named in ADR-0013's 2026-06-25 addendum. Maps a seven-stage skill lifecycle (discovery, practice, distillation, storage, retrieval, execution, evaluation/update) for the skill layer the way the Externalization survey maps the broader field. AKC's six-phase cycle overlaps this lifecycle; the delta is not the stages but loop ownership — the human approval gate — and the framing of human attention as the scarce resource.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0013-positioning-within-agent-memory-literature.md"}
+{"@id":"https://shimo4228.github.io/shimo4228/vocab#prior-art/skillsbench","sameAs":"https://www.wikidata.org/wiki/Q140352504","@type":["ExternalReference","ScholarlyArticle"],"name":"How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings","author":"Liu et al.","datePublished":"2026","identifier":"arXiv:2604.04323","url":"https://arxiv.org/abs/2604.04323","description":"Empirical corroboration named in ADR-0013's 2026-06-25 addendum. Finds that skill benefits are fragile — degrading toward the no-skill baseline as the library grows large and uncurated and the agent must retrieve from many real-world skills rather than be handed a hand-crafted one. Independent support for ADR-0010's claim that curation is the load-bearing, attention-bound act: the scarce resource is the human judgment that decides what stays, not the storage that holds it. Corroboration rather than precedent.","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0013-positioning-within-agent-memory-literature.md"}
 {"@id":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/schemas/episode-log.schema.json","@type":["CreativeWork","DataDownload"],"name":"Episode log JSON schema","description":"JSON schema for the Layer 1 episode log record. Append-only, daily-partitioned JSONL with owner-only permissions. Codifies the immutable source-of-truth shape (ADR-0002).","encodingFormat":"application/schema+json","appliesTo":"https://shimo4228.github.io/shimo4228/vocab#memory-layer/episode-log","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0002-immutable-episode-log.md"}
 {"@id":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/schemas/knowledge.schema.json","@type":["CreativeWork","DataDownload"],"name":"Knowledge store JSON schema","description":"JSON schema for the Layer 2 knowledge record. Time-decayed and forbidden-substring validated patterns distilled from Layer 1 episodes (ADR-0003).","encodingFormat":"application/schema+json","appliesTo":"https://shimo4228.github.io/shimo4228/vocab#memory-layer/knowledge","groundedIn":"https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0003-three-layer-distillation.md"}
 {"@id":"https://github.com/shimo4228/agent-knowledge-cycle/tree/main/examples/minimal_harness","@type":"SoftwareSourceCode","name":"minimal_harness reference implementation","description":"~500-line dependency-free Python reference demonstrating the three memory layers and the two-stage distill pipeline. Runs the cycle on behavioral patterns; the mechanism demo for ADR-0011 genre-neutrality (falsifiable commitment #1). Runnable end-to-end with `python3 -m examples.minimal_harness.demo`.","programmingLanguage":"Python","codeRepository":"https://github.com/shimo4228/agent-knowledge-cycle","implements":"https://shimo4228.github.io/shimo4228/vocab#concept/six-phase-loop","groundedIn":["https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0003-three-layer-distillation.md","https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0004-two-stage-distill-pipeline.md","https://github.com/shimo4228/agent-knowledge-cycle/blob/main/docs/adr/0011-cycle-applies-to-any-knowledge-body.md"]}