5,003 件 ・ 関連度順
概要と使いどころ
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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Applies Canvas brand colors, typography, and visual polish to artifacts that benefit from a consistent product look-and-feel. Use it when brand colors, style guidelines, visual formatting, or company design standards apply.
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 and fix common accessibility issues in Angular templates and Angular Material components. Use when the user mentions Lighthouse, axe, screen readers, keyboard navigation, ARIA, asks to fix a11y issues in Angular HTML templates, or after any feature, bug fix, or refactor that changed Angular templates.
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[Code Quality] Use when reviewing rationale and change quality for plans, PBIs, commits, diffs, docs, specs, reports, or explicit artifacts.
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。
[Code Quality] Use when you need restructure code without changing behavior using extract method, extract class, rename, move, and inline patterns.
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。
[Project Management] Use when you need to generate an HTML mockup report from PBI and story artifacts.
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。
[Research] Use when you need to review knowledge artifacts for completeness, citation quality, confidence accuracy, and template compliance.
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。
[Documentation] Use when you need initialize, update, or refactor CLAUDE markdown from project-config JSON and codebase scan results.
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。
Remove Gemini AI watermarks from images using GeminiWatermarkTool (GWT). Use this skill whenever the user mentions: Gemini watermark, 浮水印, AI image cleanup, removing logos from Gemini-generated images, Google ImageFX cleanup, batch processing AI-generated photos, or anything about a semi-transparent logo in the bottom-right corner of an image — even if they don't say "GeminiWatermarkTool" explicitly. Also trigger for follow-up requests like "the corner still looks dirty" or "there's still residual artifacts" after a previous removal attempt.
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, implement, and integrate generalized validation harnesses across a producer-consumer boundary after a local harness contract exists. Use when refactoring custom validation CLIs/MCPs for large polyrepos, extending Steward across sibling repos, or deploying a local tool to a consumer project for dogfooding and testing; use mcp-harness-repo-maintainer first for initial steward.yaml adoption and cold-start proof.
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 Mixture of Experts (MoE) audit on any topic, plan, codebase, evidence archive, or process. Dynamically spawns specialized subagents with different critical lenses to cross-reference findings and detect flaws, overlap, retention issues, or drift. Use when designing architectures, analyzing complex code, verifying multi-step plans, classifying evidence artifacts, or looking for duplicated intent in a repo.
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Maintains repo-local action contracts and harness repositories where product CLI and MCP adapters stay thin over core libraries. Use when adopting or improving steward.yaml actions, capability-level adoption evidence, cold-start proof loops, probes, benchmarks, CLI/MCP/core parity, adapter refactors, packages/core boundaries, or sibling harness layout; use repo-quality-system-lifecycle first for general app/library/tool stewardship baselines.
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 a ready-to-paste social post kit for an app, tool, or project launch or update — "make social posts", "launch posts", "post kit", "prep socials", "promote this". Produces one Markdown file with finished posts for X, Reddit, Instagram, LinkedIn, Threads, and short-form video, plus a pre-post checklist. Pull real facts from the project (repo, release, what it does, OS, links).
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Safely clean regenerable clutter from a project folder by scanning for build artifacts and caches, backing up every removed path into a timestamped archive with a BACKUP.md manifest, zipping the backup to save space, and only deleting originals after explicit confirmation. Use when the user asks to clean a project directory, remove node_modules, clear build output, reclaim disk space, or tidy a repo before archiving.
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 building, refactoring, or debugging a macOS menu bar app with SwiftUI, or when a MenuBarExtra misbehaves — the icon renders wrong or vanishes, the Settings window opens behind other apps, the popover cannot be closed, controls inside a .menu style do not render, the Dock icon comes back, or the app quits when the item is dragged off the menu bar. Triggers include menu bar app, status bar app, tray app, MenuBarExtra, NSStatusItem, LSUIElement, hide Dock icon.
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Retrieve the current system date and time to anchor the agent in present reality. Use for questions involving today, current time, recent events, or information newer than the model's training data to prevent knowledge-cutoff errors and fictionalization of real facts.
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Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).
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。
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
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。
Cross-disease market sizing entry skill. Triggered by user one-liner like "做 X 市场调研" or "Run market sizing for X". Auto-runs 5 phase pipeline: contract → stratify → recall → compose-audit → bundle. Hard-gates on Cite-or-Block: every fact claim must carry citation anchor verifiable against sources/. Resumable mid-run.
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。
Phase 4 Turn 1 of disease-market-sizing-orchestration. Generates report HTML with mandatory citation anchors per fact claim. Reads contract + staging + sources/. Every drug/treatment/stat/recommendation MUST carry [pmid:.../guideline:.../nct:...] anchor that resolves to an actual file in sources/. NEVER hardcode drug names or numerical claims. Use AFTER evidence recall (phase 3), BEFORE content-verification-layer (Turn 2).
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。
Cite-or-Block 架构的基石原子 skill。把报告里的 citation 锚点 (例如 [guideline:CSCO-2024-NSCLC:§5.5.2] / [pmid:12345678:abstract]) 解析为源文件片段,并核对事实声明里的关键词是否在引用源原文里出现。 Foundation atomic skill for the Cite-or-Block architecture. Resolves citation anchors (e.g. [guideline:CSCO-2024-NSCLC:§5.5.2] / [pmid:12345678:abstract]) to raw source text fragments, and verifies whether claim keywords actually appear in the cited source. 使用场景 / Use when: 1. 报告生成后要做 fact-check (resolve_citation + verify_claim_against_source) 2. content-verification-layer 要扫全报告锚点 (parse_citations_in_text) 3. drug-citation-verifier / 任何 cross-check skill 需要"锚点 → 源原文" P0 守护:本 skill **绝不维护任何已知字典**。源里没有 = verified=False, 无例外、无 fallback、无"已知答案兜底"。 P0 guard: this skill **never maintains any built-in dictionary**. Not in source = verified=False. No fallback, no built-in answers.
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 work produces a deliverable, factual claim, dataset, code change, decision, publication, deployment, automation, or irreversible action whose failure would matter; when the user asks for a quality gate, acceptance criteria, QA, completeness, validation, audit, evidence, preflight, release readiness, or a definition of done; or before claiming completion on medium- or high-risk work. Automatically decide whether a formal gate is warranted, derive task-specific pass/fail criteria, gather evidence, and block unsupported completion. Make sure to use this skill even when the user does not say "quality gate" if consequential work needs acceptance criteria or completion evidence. Skip formal gating for trivial, reversible, low-impact requests.
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。