「quick」の検索結果

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

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Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

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。

Harvests a DESIGN.md from an existing codebase, critiques it against the actual code, and applies safe quick-win fixes. Three modes harvest / critique / fix. Shells out to `npx @google/design.md lint` for structural validation; never reimplements Google's linter. The on-ramp that makes DESIGN.md adoptable for every existing repo, not just greenfield projects.

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。

Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".

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 for analytical thinking, or when a question needs breaking down and evidence: "why did metric X drop?", "what drives this?", "break this down", "what data do we need?". Builds a tree, hypotheses and evidence, ends with an answer and key uncertainty. Skip for quick verdicts.

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。

Summarize the current pull request including diff, comments, and review status. Use when reviewing a PR, preparing for a review meeting, or getting a quick PR 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。

Check GitHub Actions CI status for PRs and branches. Use when the user asks "did CI pass", "check status", "what failed", "are checks green", "PR checks", "CI status", "workflow status", "re-run jobs", or wants a quick summary of GitHub Actions runs for a PR or the current branch.

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。

Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.

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。

Implements any user intent, requirement, story, bug fix or change request by producing clean working code artifacts that follow the project's existing architecture, patterns and conventions. Use when the user wants to build, fix, tweak, refactor, add or modify any code, component or feature.

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Use on a bug, test failure, crash, or unexpected behavior — enforce reproduce → isolate → hypothesize → verify before any fix; fires even on 'this is broken' / 'quick fix'.

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。

Load this skill when configuring axe-core scans, reviewing automated accessibility test results, or writing tests that use @axe-core/playwright, @axe-core/react, or similar integrations. Provides a quick reference to axe 4.x rule IDs, their WCAG mapping, and default severity levels.

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。

[Investigation] Use when quickly locating relevant files and affected areas across a large codebase.

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] Create or describe a UI design — quick (fast), immersive (good), or recreated/described from a screenshot or video, in a product-UI or marketing/creative lane. Dispatch via --mode={fast|good|describe|screenshot|video} (default fast) and --lane={product|marketing} (default product).

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 adds a project to the workspace, opens an unfamiliar repo, asks "what is this project", "explain this codebase", or invokes explain-new-project. Explores a newly opened workspace project and writes a plain-language report for a self-taught, non-technical user—quick start (what it is + how to run) first, then optional depth—and always saves PROJECT_GUIDE.md in the project root.

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 comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.

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。

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

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 ordinary public webpages with LLM-optimized Tavily search results. Use when no specific URL is known and the user needs a quick public-web lookup, articles, recent news, sources, or domain-filtered results. This is the default Tavily leaf for simple public-web discovery. Do not use when the user already supplied the target URL (use tavily-extract), wants URLs under one known site (tavily-map), wants many pages' content (tavily-crawl), needs a full cited synthesis (tavily-research), or needs named platforms, login state, platform-native content, or cross-platform collection (Agent Reach).

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 engineering principles for making interfaces feel polished. Use when building UI components, reviewing frontend code, implementing animations, hover states, shadows, borders, typography, icons, micro-interactions, enter/exit animations, or any visual detail work. Supports quick and full review modes. Triggers on UI polish, design details, "make it feel better", "feels off", stagger animations, border radius, optical alignment, font smoothing, tabular numbers, image outlines, box shadows, icons, icon stroke weight, icon states, motion restraint.

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。

GStack design-html method for producing or planning quick HTML prototypes, design boards, or rendered visual explorations for UI review.

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。

Adversarially probe this monorepo for security flaws at the right depth. Steers the red-team subagent — picks quick/standard/deep from the request, spawns it (fanning out for a wide deep sweep), collates findings into a dated report, and files security/sec:* issues for confirmed high/critical findings. Use when asked to "red-team", "try to hack this", "find security holes", "pentest this package/app", or as the brain behind the CI + daily security runs.

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。

Solves complex, open-ended problems using a knockout tournament mechanism. Generates an initial population of diverse candidate answers, pairs them into head-to-head matches, produces a hybrid "child" solution from each pair, and advances the best of the three through a bracket until a winner emerges. Use this skill whenever the user wants to competitively select the best answer from a field of alternatives, asks for a "tournament" or "bracket" style search, wants a faster alternative to full evolutionary search, or uses phrases like: "run a tournament on this", "bracket-style search", "let solutions compete", "knockout search", "find the best answer by elimination", or "which solution wins?". Also trigger when the problem is open-ended and the user wants a clear winner quickly rather than a deep multi-generation refinement.

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。

Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick 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。

VRIO resource analysis combined with Dynamic Capabilities assessment. Use this skill to identify real competitive advantages (Barney VRIO framework), then test whether the organisation can sense new opportunities, seize them, and transform itself to stay ahead (Teece dynamic capabilities). Runs in three modes — full diagnostic for deep first-use sessions, review mode for quick re-assessment, and alert triggers for defining early-warning signals. Updates company-context.md after every run. Triggers on questions about competitive advantage, defensibility, resource assessment, why competitors are gaining ground, organisational agility, or whether advantages will hold. Based on practice by Eterdis (eterdis.com).

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。

Strategy map analysis using the Eterdis two-directional causal chain. Use this skill to diagnose whether strategy is coherent by building two chains — bottom-up from resources to results, top-down from expectations to requirements — and finding where they don't connect. Runs in three modes — full diagnostic for deep sessions, review mode for quick re-assessment, and alert triggers for early-warning signals. Updates company-context.md after every run. Triggers on questions about strategic alignment, why the strategy isn't working, what to invest in, how the business creates value, whether the plan is realistic, or where the biggest gap is. Based on practice by Eterdis (eterdis.com).

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。