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概要と使いどころ
Claude Code runtime skills router. Use when configuring SKILL.md frontmatter, discovery, invocation, hooks, context forks, substitutions, loading behavior, or headless skill dispatch.
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。
Claude Code subagent runtime and plugin-agent reference. Use when creating, configuring, or debugging subagent definitions, nested spawning, startup context, model precedence, or plugin field restrictions.
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。
Optimize existing CLAUDE.md, SKILL.md, agent definitions, and other AI-facing files for Claude comprehension and economy. Scope: optimization of existing content only — not upstream sync, not read-only auditing. Measures baseline metrics, delegates to the ai-doc-optimizer agent with file-type-specific context, runs independent verification via second agent, measures post-optimization metrics, and presents comprehensive before/after report. Supports iterative mode for large targets. Use when improving prompt effectiveness, reducing token waste, or rewriting instructions for LLM consumption. Invoke with /optimize-claude-md <file-or-directory>.
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。
Autonomous feature research and gap analysis. Use when starting /add-new-feature or analyzing existing architecture documents. Explores codebase patterns, identifies ambiguities, and produces feature-context-{slug}.md for orchestrator RT-ICA phase. Does NOT make technical decisions.
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。
Assess a plugin and produce an executable refactoring design, task plan, and context manifest. Use when preparing systematic plugin refactoring.
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。
Integrate MCP servers into Claude Code plugins — covers .mcp.json configuration, plugin.json mcpServers field, server types (stdio, SSE, HTTP, WebSocket), environment variable expansion, tool naming conventions, OAuth and token authentication, security best practices, and testing workflows. Use when adding an MCP server to a plugin, configuring MCP authentication, debugging MCP tool discovery, setting up Model Context Protocol integration, or choosing between stdio and SSE transport types.
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。
Orchestrator discipline plugin documentation index. Load when needing to read about orchestration patterns, delegation rules, or context window management.
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。
Works backward from the stated goal through its prerequisite chain — what must exist to reach the goal, then what each of those requires, back to the current state — classifying each prerequisite as AVAILABLE, DERIVABLE, or MISSING, and blocking planning until nothing is MISSING. Use before creating plans, delegating to agents, or defining acceptance criteria. Activates on specs, PRDs, tickets, RFCs, architecture designs, and multi-step engineering tasks. Always pass `#N` or an inline goal — invoking with no argument and no inline context returns BLOCKED. Integrates with CoVe-style planning pipelines.
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。
Use when all tasks for a feature are marked COMPLETE — runs holistic quality gates including code review, feature verification, integration check, documentation drift audit and update, and context refinement. Creates follow-up plans when issues are found.
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。
Analyze the causal system-wide impact of a proposed change across behavior, interfaces, state/data, runtime dependencies, tests, documentation, controls, people/processes, and model/prompt/context behavior. Use before planning when lexical reference search is insufficient to establish blast radius and verification obligations.
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。
Register a plan artifact via the MCP backlog server. Use when you produce a document or report that downstream agents or worktree-isolated environments need to retrieve — feature-context, codebase-analysis, architect, T0-baseline, TN-verification, or research artifacts. Triggers include "store an artifact", "register a plan artifact", "write a report to the backlog", "upload artifact content".
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。
Dasel v3 patterns for querying Tomcat web.xml deployment descriptors — use when inspecting servlet enumeration, filter chain discovery, listener listing, context parameter extraction, or init-param inspection in web.xml files
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。
Reviews skill, agent, and plugin artifacts against their intended consumer's schema and runtime contract. Loaded by dh:code-reviewer for SKILL.md, agent definitions, or plugin manifests; checks discovery, frontmatter, triggers, tools, context cost, bundled references, and caller handoffs.
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。
SAM-style feature initiation workflow — discovery through codebase analysis, architecture spec, task decomposition, validation, and context manifest. Use when a user asks to add a feature, plan a feature, or convert an idea into an executable SAM plan.
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。
Integrates patterns from external sources (URLs or local files) into local skills, agents, and plugins. Use when comparing external agent definitions against local equivalents, extracting best practices from frameworks like GSD or BMAD-METHOD, enhancing local skills with external workflow patterns, or adding interoperability with external tool ecosystems. Runs a 3-phase workflow — parallel candidate mapping, contextual enhancement, and validation — with source attribution and backlog tracking for deferred enhancements.
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。
Look up prior Claude Code sessions when context is lost or forgotten. Use when asked what was done before, what happened in the last session, or any request to recall past conversation history, prior decisions, experiments, or outcomes. Indexes and searches raw JSONL transcripts from ~/.claude/projects/ via DuckDB. Returns verbatim user messages, summarizes AI actions and sub-agent outcomes, detects tool errors and user frustration signals, and reports tool usage statistics. Summaries cached at ~/.claude/kaizen/session-summaries/.
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。
Dasel v3 query patterns for InstallAnywhere .iap_xml installer definitions — use when querying action sequences, discovering variables, resolving platform conditions, navigating panels, or comparing installer variants. Files are 2.5+ MB, 65,000+ lines — too large for context reads, requires structural dasel queries.
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。
Generates and commits conventional-commits messages by analyzing staged git diffs — fast and fork-context safe. Use when the user asks to commit staged changes, needs a type-scope-description message generated from the current diff, or wants scope selection guidance and pre-commit hook handling.
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。
Runs end-stage QA on a finished figure and table set. Checks callouts, numbering, and cross-references, whether numbers in the text match the exhibits, self-contained captions and statistical notes, accessibility and production quality, and links to the SI and replication package. Values that could only be read off an image are marked for author verification rather than estimated. Use when preparing a submission. Design guidance during drafting belongs to figures and tables.
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。
Reads model uncertainty from token log-probabilities. Covers collecting logprobs and aggregating multi-token labels, confidence tiers and margins for triage, calibration assessment with ECE, Brier scores, and reliability diagrams against human labels, responsible downstream use of confidence, and reproducibility archives. Use when the user asks about classifier confidence by item, logprobs, top-k tokens, calibration, ECE, Brier, reliability diagrams, or routing low-confidence cases to human review. Codebook and validation design go to text-classification.
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。
Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.
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。
OCRs scanned or image-only corpora with vision-language models in three phases. Evaluate selects a system by measured CER or WER against stratified human ground truth. Run builds the production pipeline. Clean corrects raw OCR with LLM and rule-based passes, quality diagnostics, and span-level provenance. Use when choosing an OCR model for a corpus, measuring OCR accuracy, transcribing scans at scale, or correcting raw OCR. Born-digital documents with text layers go to doc-to-markdown.
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。
Audit a manuscript's citations for fabricated sources, DOIs that resolve to the wrong work, in-text and reference-list mismatches, style, and claim support, verified against Crossref and OpenAlex. Use to check citations, references, a .bib file, or DOIs.
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。
End-stage QA for a finished figure and table set (callouts, numbering, cross-references, text-to-exhibit consistency, captions and notes, accessibility, SI and replication linkage). Use when preparing a submission.
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。