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概要と使いどころ
Deep cross-layer consistency audit for any codebase. Traces every feature from UI to database, finds broken wiring, missing handlers, model mismatches, and security gaps. Auto-fixes critical and warning issues. Use this after building features, before releases, or whenever something feels off. Works with any tech stack.
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Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
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。
Discover shadcn-compatible components and registries across the entire ecosystem before writing any custom UI. Use PROACTIVELY before building tables, forms, modals, animations, dashboards, auth pages, or any UI component. Use when the user says "find a component for...", "is there something for...", "search registries", "what exists for...", or asks about shadcn blocks, Magic UI, Aceternity, ReUI, Animate UI, DiceUI, Tailark, AI Elements, or any other shadcn-compatible registry. Complements the official shadcn skill by surfacing registries beyond the user's configured `components.json` — use when exploring what's available to add, not just what's already installed.
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。
Qualify a sales opportunity using the MEDDIC framework. Use when the user says "qualify this deal", "is this deal real", "MEDDIC qualification", "MEDDICC framework", "should I pursue this opportunity", "deal review", "how qualified is this prospect", "pipeline review prep", "forecast this deal", "sanity check on this opportunity", or wants to assess whether a sales opportunity is worth pursuing and at what pipeline stage.
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Write a compelling sales proposal. Use when the user says "write a sales proposal", "put together a proposal", "draft a proposal for this prospect", "create a business case", "write up our recommendation", "how to structure a proposal", "proposal template", "executive summary for a deal", or wants to create a written document that moves a prospect toward a decision.
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。
Write OKRs (Objectives and Key Results). Use when the user says "write OKRs", "help me set goals", "create objectives and key results", "quarterly goals", "team OKRs", "I need to define success for this quarter", "Doerr method", or wants to translate a strategic direction into measurable targets - even if they don't explicitly say "OKRs".
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 product discovery to identify what to build. Use when the user says "product discovery", "how do I know what to build", "validate this idea", "talk to customers", "are we building the right thing", "discovery process", or wants to reduce the risk of building something users don't want - even if they don't say "discovery".
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。
Manage QA release gates - go/no-go decisions, release sign-off reports, defect triage, and release readiness communication. Use this skill whenever a QA lead or manager needs to formally assess whether a build is ready to ship. Trigger on phrases like "release sign-off", "go or no-go", "is this ready to release", "defect triage", "release gate", "approve the release", "block the release", "release readiness", "quality gate", "sign off on this build", "triage these bugs", or any request to make or document a formal release decision. Also trigger when a release manager or PM asks "what's the QA status?" or "can we ship this?".
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。
Generate, score, and shortlist brand names through a guided interview. Use when the user says "name my brand", "help me name", "come up with a name", "naming ideas", "what should I call this", "brand name", "product name", "company name", "rename", "rebrand", or is stuck choosing between names. Self-contained and brand-agnostic: it does not read knowledge/, so it works for naming a brand-new venture, product, service, feature, or rebrand from scratch, before any brand context exists. Runs on Alexandra Watkins' SMILE and SCRATCH tests to generate and filter, Marty Neumeier's 7 criteria to score, and the Lexicon Branding method for sound symbolism and strategy. Asks the user questions before generating. For the positioning the name has to carry, see positioning-doc. For the message architecture built on top of it, see messaging-framework.
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 structured incident response. Use when the user says "we have an incident", "production is down", "service is degraded", "on-call response", "p0 incident", "something is broken in prod", "help me manage this incident", "incident commander", or there is an active production issue requiring coordinated response - even if they don't explicitly say "incident response".
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。
Debug a bug or unexpected behavior systematically. Use when the user says "there's a bug", "this isn't working", "I'm getting an error", "help me debug", "why is this failing", "unexpected behavior", "test is failing", "something is broken", or describes behavior that doesn't match expectations - even if they don't say "debug".
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 team health using Patrick Lencioni's Five Dysfunctions of a Team model. Use when a leader says "my team feels off", "we have trust issues", "people aren't speaking up in meetings", "accountability is a problem", "we keep missing commitments", "the team is siloed", "we're not working well together", or "I want to do a team health check". Also trigger when someone describes symptoms like passive agreement in meetings, blame culture, missed deadlines without escalation, or people optimizing for their own metrics over team goals.
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。
Deliver feedback using Kim Scott's Radical Candor framework - care personally while challenging directly. Use when a leader needs to give difficult feedback, says "I need to tell someone something hard", "how do I give feedback without hurting them", "I've been avoiding a conversation", "my direct report isn't performing", "someone on my team has a blind spot", "I keep sugarcoating things", or "how do I be honest without being a jerk". Also trigger when someone describes being too nice (ruinous empathy) or too harsh (obnoxious aggression), or when they describe avoiding a conversation they know they need to have.
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。
Write a high-performing LinkedIn post in the user's brand voice using Hook-Story-Offer (Russell Brunson) and the Curiosity Gap hook method (George Loewenstein). Every post starts by selecting a named hook formula - specific number + surprising result, contrarian statement, personal confession, direct challenge, or before/after. Use when the user asks for a LinkedIn post, LinkedIn update, LinkedIn content, "post for LinkedIn", thought-leadership post, founder post, or short professional social content. Reads brand voice and ICP from knowledge/ so output sounds like the company, not generic AI. For long-form opinion pieces, see thought-leadership-writer. For the monthly posting plan, see social-calendar. For turning one asset into many posts, see content-repurposer.
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 whether your leadership behaviors amplify or diminish your team using Liz Wiseman's Multipliers framework. Use when a leader asks "am I a good manager", "why isn't my team performing at their potential", "I feel like I'm doing all the thinking for my team", "my team seems dependent on me", "I want to be a better leader", "how do I empower my people", or "my team is smart but underperforming". Also trigger when someone describes always having the best ideas in the room, team members not taking initiative, reports waiting for direction before acting, or a leader who feels exhausted from carrying the team. Diminisher patterns are often invisible to the leader exhibiting them.
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。
Write a consulting engagement proposal. Use when a consultant says "write me a proposal", "draft a proposal for [your client]", "I need to send a proposal", "how do I structure a proposal", "client wants a SOW", "write a statement of work", "I need to propose a project", or "help me price and scope this engagement". Also trigger when someone describes a client conversation that ended with "send me something in writing".
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。
Convert Confluence pages to clean GitHub-Flavored Markdown files. Use this skill whenever the user wants to pull a Confluence page into the local repo, convert Confluence content to markdown, download a spec from Confluence, or batch-convert multiple pages. Also triggers on Confluence URLs, page IDs, or phrases like "pull this page", "download this spec", "confluence to md". Use this even if the user just pastes a Confluence URL and says something vague like "get this" or "convert this".
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。
Design statistically rigorous experiments to test data science hypotheses. Use when the user says "design an A/B test", "run an experiment", "test this hypothesis", "is this difference significant", "how many samples do I need", "randomized controlled trial", "causal inference", "uplift test", "holdout group", "significance test", "power calculation", "avoid p-hacking", or needs to determine whether an observed effect is real before making a product or model decision.
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。
Set a repo up to prove engineering-task work actually works before it ships. Investigates the repo, ensures a one-command dev stack (`dev-local`) exists, asks whether verification runs locally or in a sandbox (crabbox), confirms/installs the driver (the `playwright-cli` skill for web by default). Outputs three artifacts: a committed `/verify` skill (per-task verification SOP — spawn a verifier sub-agent → drive the app → screenshot/video proof → open a PR with the proof embedded), the `/dev-local` skill + script, and the installed driver skill. Use when someone says "set up verification", "make this repo verifiable", "scaffold a verify skill", "set up the verifier".
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。
Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.
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 deciding WHERE to point SEO effort, not how to write a page. Triggers: a new site or brand with no rankings and no authority ("cold start", "starting from zero", "nobody knows us"), deciding what to double down on, a page or cluster that ranks but earns nothing, hunting emerging or newly-coined keywords before competitors arrive, "should we build a cluster or one page", "what do we write next", "we get impressions but no clicks", "our traffic plateaued despite publishing", whether to chase a head term at all, or turning any of it into recurring automation. Also use when asked why an SEO effort stalled despite consistent output. NOT for writing an article, keyword expansion mechanics, or auditing a single tactic for penalty risk.
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 Hermes Agent to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Hermes without changing the generated Python harness format.
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 OpenClaw to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to OpenClaw without changing the generated Python harness format.
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 Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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。