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概要と使いどころ
Explain and apply the foundational LLM Wiki architecture and knowledge-management strategy. Use for setup, architecture, schema, or organization decisions; operational ingest/query/lint work uses dedicated skills.
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Archive and rebuild wiki knowledge from source, or restore a prior archive. Use for full restart/recovery when incremental repair is inappropriate; this is broader and more destructive than ordinary update or lint.
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Find recurring concept combinations across the wiki that lack an explicit synthesis page, then create cross-cutting synthesis pages. Use for knowledge synthesis after the vault has accumulated enough material.
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Ingest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining ~/.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.
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Ingest GitHub Copilot CLI/session history into Obsidian as distilled knowledge. Use for importing or mining Copilot history; not for general Copilot help, simple session search, or backup.
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Create a reviewable Agent Skill package from mature curated wiki pages. Use when turning verified vault knowledge into a reusable skill. Reads the vault and writes only to a review directory; it does not install skills.
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Sync knowledge from the current project into the Obsidian wiki. Use when work already in the current project should be distilled into the vault; named-vault routing includes @work update wiki. wiki-capture saves the current conversation and wiki-ingest handles external/new sources.
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Report wiki ingestion/completeness state, pending source delta, structural insights, or maintenance equilibrium. Use for remaining-work/status questions, hubs and bridges, or whether maintenance skills still have pending changes. wiki-digest summarizes learned knowledge instead.
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Search and synthesize answers from the compiled Obsidian wiki, including cited and multi-hop answers. Use for questions about existing wiki knowledge or fast index-only lookups. Supports named-vault routing such as wiki-query @work; not for ingesting new sources.
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Ingest Claude Code conversation/session history into Obsidian as distilled knowledge. Use for importing or mining past Claude sessions, .claude data, project/session history, or audit logs.
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Ingest Codex CLI conversation/session history into Obsidian as distilled knowledge. Use for importing or mining ~/.codex sessions, rollout files, indexes, or transcript logs; use wiki-agent for targeted topic-only recall.
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Ingest OpenClaw session/history data into Obsidian as distilled knowledge. Use for importing or mining ~/.openclaw sessions, memory files, or logs; use wiki-agent for targeted topic-only cross-agent recall.
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Perform multi-round web research on a topic, synthesize the findings, and file structured results into the Obsidian wiki. Use for comprehensive web-sourced research intended to become wiki knowledge.
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Apply plugin knowledge base updates to an existing generated system. Consults the Ars Contexta research graph for methodology improvements, proposes skill upgrades with research justification. Never auto-implements. Triggers on "/upgrade", "upgrade skills", "check for improvements", "update methodology".
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Re-derive your knowledge system from first principles when structural drift accumulates. Analyzes dimension incoherence, vocabulary mismatch, boundary dissolution, and template divergence. Preserves all content while restructuring architecture.
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Challenge system assumptions against accumulated evidence. Triages observations and tensions, detects patterns, generates proposals. The scientific method applied to knowledge systems. Triggers on "/rethink", "review observations", "challenge assumptions", "what have I learned".
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Research-backed evolution advice for your knowledge system. Analyzes health reports, friction patterns, and derivation history to propose specific changes with research justification. Never auto-implements — proposals require your approval.
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Interactive knowledge graph analysis. Routes natural language questions to graph scripts, interprets results in domain vocabulary, and suggests concrete actions. Triggers on "/graph", "/graph health", "/graph triangles", "find synthesis opportunities", "graph analysis".
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Extract structured knowledge from source material. Comprehensive extraction is the default — every insight that serves the domain gets extracted. For domain-relevant sources, skip rate must be below 10%. Zero extraction from a domain-relevant source is a BUG. Triggers on "/reduce", "/reduce [file]", "extract insights", "mine this", "process this".
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Show vault statistics and knowledge graph metrics. Provides a shareable snapshot of vault health, growth, and progress. Triggers on "/stats", "vault stats", "show metrics", "how big is my vault".
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Add a new knowledge domain to your existing system. Derives domain-specific configuration through conversation, generates domain folders, templates, and vocabulary while preserving and connecting to your existing architecture.
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Research a topic and grow your knowledge graph. Uses Exa deep researcher, web search, or basic search to investigate topics, files results with full provenance, and chains to processing pipeline. Triggers on "/learn", "/learn [topic]", "research this", "find out about".
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Golang refactoring — safe, at-scale restructuring of existing Go code: a coverage-adaptive safety net, behavior-preserving transforms (gopls Rename/Extract, `gofmt -r`, `gopatch`), the Fowler catalog mapped to Go, breaking import cycles, and small stacked PRs. Apply when a function or type has grown too large, a code smell blocks a feature, or the user asks to refactor Go code — also for renaming at scale, extracting functions or interfaces, moving code between packages, or planning a multi-step refactor. Target styles owned elsewhere → See `samber/cc-skills-golang@golang-naming` (renames), `samber/cc-skills-golang@golang-project-layout` (splits), `samber/cc-skills-golang@golang-modernize` (idioms), `samber/cc-skills-golang@golang-code-style` (control flow), `samber/cc-skills-golang@golang-design-patterns` (patterns/DI).
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[omh] Blocked on a project by a knowledge gap: just-in-time learning workflow: select and confirm an immediate learning target, research credible sources, and prepare an application-first brief without popularity ranking. Use when the user says: jit-learn, learn next, learn now, blocker-specific learning target, highest-leverage learning target, immediate learning payoff, immediately applicable learning brief, source-backed learning brief.
日本語の概要は準備中です。原文の説明を表示しています。