8,100 件 ・ 関連度順
概要と使いどころ
Compile up to five durable insights from the current conversation for possible addition to CLAUDE.md. Use before clearing context, when asked to remember lessons, or when the user wants project conventions and preferences preserved.
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。
Save the latest learning as a numbered markdown file under ~/.claude/learnings and update the learnings index with title and tags. Use when the user says "save", asks to record a learning, or wants the current insight stored for later.
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。
Split user stories into smaller, independently deliverable slices using the SPIDR method (Spike, Path, Interface, Data, Rules). Use this skill whenever the user asks to split a story, break down work, slice a story, asks "can this be split", mentions "SPIDR", says "story splitting", or wants to decompose a large ticket into smaller pieces. Also trigger when a user presents a story that seems too large for a single sprint and asks for help sizing or scoping it.
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。
Gauntlet for absolute claims (always/never/guaranteed/optimal); pressure-test, then refine with explicit boundaries. Use when users ask to prove or disprove strong certainty claims, request devil's-advocate challenge rounds, or want the /tw-prove-it gauntlet to run all 10 rounds continuously by default.
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。
Run one explicit escalation pass using the original glaze prompt words verbatim. Use when prompts say `/tw-glaze`, when the first answer feels merely adequate, or when you want the exact original rhetoric preserved while pushing for a materially stronger direction.
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。
Compile deep repository evidence into artifact-bound correctness doctrine — authority/law/proof maps, owned invariants, failure archaeology, and the strongest durable destination for each piece of knowledge, plus an optional minimal repository-specific skill portfolio. Use when the user wants both deep codebase understanding AND durable doctrine, knowledge routing, or repo-specific skill recommendations. Research discoverable facts before asking. Read-only. Not for quick onboarding, one isolated invariant, ordinary implementation, generic review, or direct skill creation.
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。
Brutally honest AGENTS.md/CLAUDE.md review backed by real A/B test evidence. Not just opinions — actual proof that your rules are dead weight. Roasts instruction files for bloat, slop, and redundancy, then proves it by running evals. Use when user says "roast my agents.md", "roast my CLAUDE.md", "prove my rules are useless", "eval roast", or wants entertaining evidence-based feedback on their AI config files. Also triggers on "audit my instructions" or "are my rules helping".
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。
Commit the current changes with quality checks, status review, staged diff inspection, appropriate tests, and a clear commit message. Use when the user says "commit", "c", asks to make a commit, or wants changes saved in git.
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。
Run a second, harder escalation pass using the original glazer prompt words verbatim. Use when prompts say `/tw-glazer`, when a first escalation still feels incremental, or when you want the exact original rhetoric preserved while forcing a sharper replacement rather than more polish.
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。
Inspect a reference (web URL, image, PDF, screenshot) and propose a candidate Style for the workspace. Use when the user says "save this style", "guarda este estilo", or shares a reference and wants to reapply it later.
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。
Apply a Style to any artifact in the workspace (presentation, card, poster, social post, web page). Use when the user says "apply style X", "render this with style X", or wants to reuse a saved style on a new piece.
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。
Produce variants of an existing Style by shifting tone (light/dark), density (compact/relaxed), or accent (palette rotation) while preserving the brand identity. Use when the user wants alternate themes derived from one brand.
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-localize subscription and in-app purchase display names across all App Store locales using asc. Use when you want to fill in subscription/IAP names for every language without clicking through App Store Connect manually.
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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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。
Implement one scoped slice using TDD red-green-refactor. Use when ready to write code for a defined slice of work, or when the user wants test-driven development.
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。
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
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。
Throwaway design probe for logic, state models, UI variations, and affordances before production work. Use when the user wants to prototype, sanity-check a model, make something playable, compare UI directions, or explore a design before ln-spec/ln-plan/ln-scope.
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。
Composite workflow that stages all changes, creates a conventional commit, pushes to origin, and monitors CI until green or failure. Use when you want to commit and push in one step with CI monitoring. Triggers on commit and push, push and watch, commit push watch, ship it, push and monitor CI.
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。
Create a pull request from the current branch. Triggers on create PR/open PR/make PR/submit PR/push PR/raise PR/open a pull request/create a pull request/ready to merge/branch is ready when the user wants to turn their current branch into a GitHub pull request with a well-structured description
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 current repo structure, build system, test setup, and conventions to provide a practical onboarding guide. Use when new to a codebase, joining a project, or wanting to understand how a repo is organized. Triggers on getting started, new to repo, onboard, how does this repo work, repo structure, codebase overview.
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。
Guidance on writing high-quality requirements: the requirement quality characteristics and the EARS (Easy Approach to Requirements Syntax) patterns — ubiquitous, event-driven, state-driven, optional-feature, unwanted-behaviour — for unambiguous, singular, verifiable requirements, plus defect/anti-pattern review and verification & traceability. Use when authoring or reviewing requirements. Original synthesis citing EARS (Mavin et al.) and NASA public-domain guidance; not a reproduction of ISO/IEC/IEEE 29148 or the EARS paper.
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。
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrase -- including German ones such as "grill mich", "grill mich zu diesem Plan" or "zerpflück meinen Plan im Grill-Modus". Entry point for the /grill-me command; can also be invoked directly.
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。
Neutrale moralisch-rechtliche Prüfinstanz für Politik und Entscheidungen — der lauffähige Prototyp des Forschungsprojekts "Die Position der Ungeborenen" (Schattenmodus Stufe 1). Nutze diesen Skill, wann immer eine politische Entscheidung, ein Gesetz(entwurf), eine Reform, ein Haushaltsbeschluss oder eine gesellschaftliche Streitfrage analysiert, geprüft oder begutachtet werden soll — auch bei Formulierungen wie "prüfe aus Sicht künftiger Generationen", "Gesetzespass", "was sagt das Grundgesetz dazu", "Superposition-Prüfung", "Gesetzesgeschichte/Containeranalyse", "Folgenabschätzung", "analysiere diese Reform", "lebende Verfassung" oder wenn der User eine Politik-Fragestellung mit Bitte um neutrale, mehrstufige Bewertung einbringt. Orchestriert die 5-CORE-Architektur (config.json): moralische Superposition-Instanz, Gesetzbuch-Verkörperungen, zweistufige Folgenabschätzung (retrospektiv/prospektiv mit Evidenzhierarchie), Wissens-Handler mit lokalem Speicher, einstellbarer Workflow.
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 the user wants to send the same prompt to several LLMs and compare the answers - sequentially (stopwatch, clean per-lane timing) or in parallel (true race), with optional repetitions per model, judged by the starting model across quality, correctness, completeness, instruction fidelity and latency (time is only one dimension). Triggers on /compare-race, 'model race', 'vergleiche modelle', 'gleicher prompt an mehrere modelle'.
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。