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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。

Test harness for Claude Code skill argument substitution — demonstrates capture-block pre-declaration, XML tag referencing, unintentional variable corruption in code blocks, and correct placement of shell examples in reference files. Use when verifying substitution behavior before applying a pattern to other skills, testing how arguments flow from skill invocations, or understanding the pre-declaration and reference file pattern with greet/farewell/inspect actions.

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。

Badge design and selection knowledge base for shields.io badges in README files. Use when writing or updating READMEs, choosing badge layouts, selecting badge styles, adding project health indicators, or picking Simple Icons logo slugs. Covers shields.io URL encoding rules, static vs dynamic badge selection, style variants (flat/flat-square/for-the-badge/social/plastic), layout patterns (two-tier/inline/centered), project-type badge sets for Python/JS/Rust/Claude plugins, color reference, non-obvious logo slugs, and common anti-patterns to avoid.

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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。

Enforce anti-AI UI design rules based on the Uncodixfy methodology. Use when generating HTML, CSS, React, Vue, Svelte, or any frontend UI code. Prevents generic AI aesthetic — soft gradients, glassmorphism, hero sections in dashboards, oversized rounded corners, and decorative copy. Applies constraints from Linear/Raycast/Stripe/GitHub design philosophy for functional, honest, human-designed interfaces. Triggers on UI generation, dashboard building, component creation, CSS styling, landing page design, or any task producing visual interface code.

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Creates a GitHub milestone on the current repository and returns its number for downstream use. Use when starting a new sprint, release, or theme grouping of backlog items. No args triggers guided intake (title, due date, description); 'quick {title}' skips to description only. Checks for duplicates before creating. Returns milestone number for /group-items-to-milestone.

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 git branches and generate structured MR/PR descriptions with domain-based change categorization — bug fixes, enhancements, technical debt, documentation, testing, build/CI, and non-functional changes. Use when preparing merge request descriptions, pull request bodies, writing changelogs from git diffs, documenting branch changes, or generating release notes. Works with GitHub and GitLab without requiring JIRA or issue tracker integration.

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Explains Chain of Verification (CoVe) prompt design — a 4-step pattern separating generation from independent factual verification. Use when designing prompts that require factual accuracy, reducing hallucinations, checking technical standards or APIs, or producing step-by-step procedures where subtle errors are costly.

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Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.

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Manages the research/ knowledge base of verified tool and library research entries via knowledge-explorer.py. Commands — list (browse by category or SDLC layer), fetch-github (draft entry from GitHub repo), add (validate and route to category dir), update-append (append dated revision), generate-descriptions (repair missing or low-quality descriptions), migrate (convert inline-header entries to frontmatter). Use when browsing KB topics, adding or updating research entries, fetching GitHub repo metadata, generating descriptions in parallel via Haiku subagents, or migrating old-format entries to skill-spec frontmatter.

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。

Assign backlog items to a GitHub milestone by bridging per-item files to GitHub Issues. Use when populating a sprint or release milestone, after create-milestone, or when a milestone number is specified with optional P0/P1/P2 or title filter. Creates missing GitHub Issues for selected P0/P1 items, assigns all selected items to the milestone, and updates Project V2 Status to Backlog.

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Analyze git repository history to produce a codebase risk profile before code review. Probes repo size, runs 7 parallel git analysis pipelines (hotspots, bug magnets, bus factor, contributor momentum, firefighting frequency, newly added files), cross-references hotspots with bug magnets to identify high-risk files with primary owner annotation, and writes walkthrough/recon-report.md. Use before code review to prioritize reviewer attention, at the start of linear-walkthrough Phase 1 Discovery to weight file coverage, or when onboarding to an unfamiliar codebase.

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Install and configure the GitHub CLI (gh) for AI agent environments where gh may not be pre-installed and git remotes use local proxies instead of github.com. Use when gh command not found, shutil.which returns None, need GitHub API access for issues or PRs or releases or workflow runs, or repository operations fail with 'failed to determine base repo' error. Provides auto-install script with SHA256 verification, GITHUB_TOKEN auth with anonymous fallback, and the required -R flag pattern for proxy environments. Covers project management via GitHub Projects V2, milestones via REST API, issue lifecycle templates, and label taxonomy management.

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Verifies claims in backlog items, skill documentation, or plugin content against primary sources using web lookups. Spawns parallel verification agents that must use WebFetch/WebSearch/gh — training data recall is explicitly rejected as evidence. Produces VERIFIED/REFUTED/INCONCLUSIVE verdicts with citations. Use when items are marked UNVERIFIED or when verifying tool API claims, CLI flags, or documented software behavior.

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。

Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.

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Close a completed GitHub milestone and generate a completion summary. Use when a sprint or release is finished and needs to be officially closed. Audits open and closed issues, offers to carry forward open items to a new or existing milestone, closes the milestone, updates Project V2 Status to Done for closed issues, and produces a completion report.

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。

Browser automation for AI agents using the agent-browser CLI and Playwright. Use when navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, logging into sites, or automating any browser task. Triggers on "open a website", "fill out a form", "click a button", "scrape data", "test this web app", "automate browser actions", or any programmatic web interaction request.

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This skill should be used when the user asks to "lint bash script", "run shellcheck", "format shell script", "use shfmt", "fix shellcheck errors", or mentions shell script linting, formatting, code quality, or pre-commit hooks for bash.

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This skill should be used when analyzing Claude Code session transcripts, reviewing agent performance, finding anti-patterns or tool misuse, mining workflow patterns, running kaizen analysis, debugging agent behavior, or performing session forensics.

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。

Builds comprehensive Claude Code skills using parallel research agents — categorization, parallel documentation gathering, anti-hallucination checkpoints, and final validation. Use when building a skill from official docs, when "research for skill" or "create comprehensive skill" is requested, or when extensive multi-source documentation gathering is needed before skill creation.

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Orchestrate research entry lifecycle in ./research/ — create, batch-import, refresh stale entries, and validate structure. Use when asked to add a tool, research a URL, document a library, refresh research, validate entries, or given any tool or library URL. Supports --batch (parallel multi-URL), --rerun (refresh one or all entries), and --validate (structural check with auto-fix of error-severity issues).

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。

Bulk-refresh research entries in ./research/ using parallel research-curator agents. Use when /refresh-research is invoked, stale research needs updating, or bulk re-verification of research entries is requested. Inventories entries by review date and age, runs RT-ICA pre-flight, spawns agents in waves of 5, then validates, reviews, and commits through research-curator. Supports --all, --stale, --category, --layer, and --dry-run flags.

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Transforms validated /linear-walkthrough artifacts into one presentation-ready deck outline per major codebase component. Use when the user asks to create a presentation, prepare a walkthrough deck, build an onboarding deck, produce an architecture review deck, or summarize a codebase for a technical audience. Requires walkthrough directory output -- reads unified walkthrough, per-section files, validation reports, coverage maps, entry points, and open questions -- then orchestrates four parallel agent phases to produce slide outlines with speaker notes, evidence references, and suggested visuals.

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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。