前端開發

Analyze and enhance Makefiles for complete user functionality coverage. Triggers: Makefile analysis, Makefile gaps, missing targets, plugin release, Makefile coverage, build targets, make dogfood, plugin quality Use when: analyzing Makefile completeness before releasing plugins, identifying gaps during plugin maintenance, scoring Makefiles against best practices, verifying Makefiles support standard developer workflows DO NOT use when: writing initial Makefiles from scratch. DO NOT use when: debugging specific build target failures. DO NOT use when: creating custom non-standard build systems. Use this skill BEFORE releasing any plugin to verify Makefile coverage.

Use a Layered (N-Tier) architecture to separate presentation, domain logic, and data access responsibilities within a system. Triggers: layered architecture, n-tier, separation of concerns, presentation layer, data access layer, service layer, traditional architecture, monolith structure, layer enforcement, dependency direction Use when: building traditional applications with clear boundaries, working with moderate-sized teams, needing familiar and well-understood patterns, compliance requirements demand clear separation DO NOT use when: selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: high scalability needs independent component scaling. DO NOT use when: teams need independent deployment cycles - use microservices. Consult this skill when implementing layered patterns or enforcing layer boundaries.

Enforces "prove before claim" discipline - validation, testing, and evidence requirements before declaring work complete. Triggers: completion, finished, done, working, should work, configured, ready to use, implemented, fixed Use when: claiming ANY work is complete, recommending solutions, stating something will work, finishing implementations DO NOT use when: explicitly asking questions or requesting clarification DO NOT use when: work is clearly in-progress and not claiming completion CRITICAL: This skill is MANDATORY before any completion claim. Violations result in wasted time and eroded trust.

Systematically uncover and fix bugs using language-specific expertise and reproducible evidence. Triggers: bug hunting, defect detection, debugging, fix verification, bug fix, regression check, error investigation, defect documentation Use when: deep bug hunting needed, documenting defects, verifying fixes, systematic debugging required DO NOT use when: test coverage audit - use test-review instead. DO NOT use when: architecture issues - use architecture-review. Use this skill for systematic bug hunting with evidence trails.

Detect codebase bloat through progressive analysis: dead code, duplication, complexity, and documentation bloat. Triggers: bloat detection, dead code, code cleanup, duplication, redundancy, codebase health, technical debt, unused code Use when: preparing for refactoring, context usage is high, quarterly maintenance, pre-release cleanup DO NOT use when: actively developing new features, time-sensitive bug fixes. DO NOT use when: codebase is < 1000 lines (insufficient scale for bloat). Progressive 3-tier detection: quick scan → targeted analysis → deep audit.

Evaluate and upgrade test suites with TDD/BDD rigor, coverage tracking, and quality assessment. Triggers: test audit, test coverage, test quality, TDD, BDD, test gaps, test improvement, coverage analysis, test remediation Use when: auditing test suites, analyzing coverage gaps, improving test quality, evaluating TDD/BDD compliance DO NOT use when: writing new tests - use parseltongue:python-testing. DO NOT use when: updating existing tests - use sanctum:test-updates. Use this skill for test suite evaluation and quality assessment.

Scope-focused PR code review that validates against original requirements and routes out-of-scope findings to GitHub issues. Triggers: PR review, pull request review, scope validation, requirement compliance, backlog triage, code review, blocking issues Use when: reviewing PRs, validating against requirements, triaging findings to backlog, preventing overengineering DO NOT use when: preparing PRs - use pr-prep instead. DO NOT use when: deep code review - use pensive:unified-review. Use this skill for scope-focused PR reviews.

detailed hook evaluation framework for Claude Code and Agent SDK hooks. Triggers: hook audit, hook security, hook performance, hook compliance, SDK hooks, hook evaluation, hook benchmarking, hook vulnerability Use when: auditing existing hooks for security vulnerabilities, benchmarking hook performance, implementing hooks using Python SDK, understanding hook callback signatures, validating hooks against compliance standards DO NOT use when: deciding hook placement - use hook-scope-guide instead. DO NOT use when: writing hook rules from scratch - use hookify instead. DO NOT use when: validating plugin structure - use validate-plugin instead. Use this skill BEFORE deploying hooks to production.

Update documentation with writing guideline enforcement, consolidation detection, and accuracy verification. Triggers: documentation update, docs update, ADR, docstrings, writing guidelines, readme update, debloat docs Use when: updating documentation after code changes, enforcing writing guidelines, maintaining ADRs DO NOT use when: README-specific updates - use update-readme instead. DO NOT use when: complex multi-file consolidation - use doc-consolidation. Use this skill for general documentation updates with built-in quality gates.

Transform tool-heavy workflows into MCP code execution patterns for token savings and optimized processing. Triggers: MCP, code execution, tool chain, data pipeline, tool transformation, batch processing, workflow optimization Use when: >3 tools chained sequentially, large datasets (>10k rows), large files (>50KB), context usage >25% DO NOT use when: simple tool calls that don't chain. DO NOT use when: context pressure is low and tools are fast. Use this skill BEFORE building complex tool chains. Optimize proactively.

Competence in data analytics and machine learning, enabling developers to build data-driven features and integrate AI/ML capabilities.

TDD方法論に従ってテストを作成します。テストファイルの配置（コロケーション）、命名規則、テスト構造のベストプラクティスに従います。React/TypeScript、Go、Rustで適切なパターンを使い分けます。「テストを書いて」「テストを作成」「単体テストを追加」などのリクエストで起動します。

Use when user wants to execute long-running tasks that require multiple sessions to complete. This skill manages task decomposition, progress tracking, and autonomous execution using Codex non-interactive mode with auto-continuation. Trigger phrases include autonomous, long-running task, multi-session, 自主执行, 长时任务, autonomous skill.

Command-line tool for managing TiddlyWiki files. Use when working with TiddlyWiki (.html) files, tiddlers, or when the user mentions TiddlyWiki operations.

Generate images using Nano Banana Pro (Gemini 3 Pro Preview). Use when creating app icons, logos, UI graphics, marketing banners, social media images, illustrations, diagrams, or any visual assets. Supports reference images for style transfer and character consistency. Triggers include phrases like 'generate an image', 'create a graphic', 'make an icon', 'design a logo', 'create a banner', 'same style as', 'keep the style', or any request needing visual content.

Expert guidance on Swift Concurrency concepts. Use when working with async/await, Tasks, actors, MainActor, Sendable, isolation domains, or debugging concurrency compiler errors. Helps write safe concurrent Swift code.

Guide for creating, auditing, and packaging Claude Code skills. This skill should be used when building new skills, improving existing skills, understanding skill structure, or packaging skills for distribution.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

Step-by-step guide for adding support for a new AI editor format to PRPM - covers types, converters, schemas, CLI, webapp, and testing

Expert guidance for creating Claude Code slash commands with correct frontmatter, structure, and best practices