1.3万 件 ・ 関連度順
概要と使いどころ
Guide for testing conventions and CI pipelines — unit tests, integration smoke tests, pytest markers, and GitHub Actions workflows. Use when the user asks about testing, CI, running tests, or adding tests for a recipe.
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。
Behavioral guardrails for implementation work. Reduces common LLM coding mistakes: overcomplication, silent assumption-picking, scope drift, and unverifiable success criteria. Load on Builder and software-engineer-mode.
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 immediately after RBR confirms a root cause, or after any confirmed finding from security-audit-lens, legacy-investigation-lens, a scan skill, or a Critical/Required code-review finding, before considering the finding complete. Checks whether the confirmed defect is one instance of a structurally identical pattern elsewhere in the same file family, workflow, or business-domain area, and folds in or explicitly defers every other instance found. Mandatory for Architect — not an optional lens the agent judges when to 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。
Context-survival and proactive-iteration extensions. Always-on. Covers Working Buffer Protocol, Compaction Recovery, Relentless Resourcefulness, and Self-Improvement Guardrails.
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: investigating a legacy, inherited, third-party-built, or otherwise newly-unfamiliar codebase before scoping a migration or major refactor. Formalizes a repeatable five-step investigation pass — entry-point census, business-rule classification, side-effect/idempotency cataloging, implicit-contract discovery, semantic-duplication detection — plus a canonical per-project Open Questions document. Requires checkable signals: ticket keywords or prior documentation gaps. Not a mandatory gate; reserved for entry-point-heavy work in code areas with no prior investigation record.
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: analysing a project's test health — coverage, robustness, and CI integration.
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。
Universal guardrails loaded by every agent. Defines Verify Before Reporting (VBR), Write-Ahead Log (WAL), and the security baseline. Always-on, role-independent.
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: UI standards discovery, UI pattern research, UI audit, pre-handoff UI state coverage review, or when a business-specific child skill needs a stack-agnostic UI methodology to load first.
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。
Shared foundation for all human-voice writing skills. Load before any profession-specific skill. Contains: burstiness principle, perplexity principle, soul injection techniques, community-discovered AI patterns with sources, additional core patterns, banned AI vocabulary, and scoring rubric.
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Convergence loop that iteratively improves work until quality thresholds are met. Scores, diagnoses specific weaknesses, rewrites, re-scores, and repeats until all dimensions reach 8/10 or diminishing returns are detected. Use when you want to refine or iterate on work, after the analyst gives a REVISE verdict, or when output quality is below your bar. Part of the architect-system loop. Outputs to system/refinery-log.md.
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 and review iOS 26+ SwiftUI Liquid Glass UI. Use when adopting Liquid Glass or checking its correctness, performance, and design fit.
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, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
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。
No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points. This skill covers when to use which platform, how to build reliable automations, and when to graduate to code-based solutions. Key insight: Zapier optimizes for simplicity and integrations (7000+ apps), Make optimizes for power
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。
React Native performance and architecture guidelines from Vercel 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。
Build communication features with Twilio: SMS messaging, voice calls, WhatsApp Business API, and user verification (2FA). Covers the full spectrum from simple notifications to complex IVR systems and multi-channel authentication. Critical focus on compliance, rate limits, and error handling. Use when: twilio, send SMS, text message, voice call, phone verification.
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。
This skill should be used when the user asks to "identify web application vulnerabilities", "explain common security flaws", "understand vulnerability categories", "learn about injection attacks", "review access control weaknesses", "analyze API security issues", "assess security misconfigurations", "understand client-side vulnerabilities", "examine mobile and IoT security flaws", or "reference the OWASP-aligned vulnerability taxonomy". Use this skill to provide comprehensive vulnerability definitions, root causes, impacts, and mitigation strategies across all major web security categories.
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。
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
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When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging strategy.
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。
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
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。
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
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。
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.
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。
Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.
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。
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
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 this skill when writing, rewriting, or improving marketing copy for any page (homepage, landing page, pricing, feature, product, or about page). This skill produces clear, compelling, and testable copy while enforcing alignment, honesty, and conversion best practices.
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。