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Smart repo bootstrapping for Agentic flow (AGENTS.md)
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Smart repo bootstrapping for Agentic flow (AGENTS.md)
Create or resume an execution plan - a design document that a coding agent can follow to deliver a working feature or system change
Smart and conventional Git commits
This skill should be used when the user asks about "Ba", "knowledge sharing context", "enabling context for collaboration", "originating ba", "dialoguing ba", "systemizing ba", "exercising ba", "creating space...
This skill should be used when the user asks about "SECI model", "knowledge creation cycle", "tacit vs explicit knowledge", "knowledge conversion", "GRAI framework", "human-AI knowledge collaboration", "sociali...
This skill should be used when the user asks about "knowledge assets", "capturing knowledge", "organizational memory", "experiential knowledge", "conceptual knowledge", "systemic knowledge", "routine knowledge"...
This skill should be used when the user asks to "extend knowledge-manager", "create a knowledge management plugin for Notion/Obsidian/Linear", "implement SECI for a specific tool", "build a knowledge adapter",...
This skill should be used when the user asks about "Notion knowledge management", "SECI in Notion", "documenting in Notion", "organizing knowledge in Notion", "Notion database architecture", "PARA in Notion", "...
This skill provides guidance on designing effective evaluation rubrics. Use when: - Creating criteria for content or code quality assessment - Defining weights and thresholds for evaluation - Designing check ty...
This skill provides common evaluation patterns and integration guidance. Use when: - Integrating eval-framework with other plugins - Designing evaluation workflows - Choosing between content vs behavior evaluat...
This skill should be used when the user asks about "Notion icons", "page icons", "emoji icons", "icon consistency", "visual organization", "icon meaning", "database icons", "icon color coding", "meaningful icon...
Handle MetaMask signature and transaction popups during Web3 DApp testing - approve signatures, send transactions, call contracts. Detects popup type and handles gas errors.
Set up MetaMask wallet extension for Web3 DApp testing - download extension, import wallet from private key. Run at test start if tests/config.yaml has web3.enabled=true.
Generate test report with clear visual indicators - ✅ for pass, ❌ for fail. Summarize results, document failures, provide recommendations.
Generate persistent test cases from project analysis, or add individual test cases interactively. Supports full project analysis or adding single test cases via prompt description with browser exploration.
Execute tests from persistent test cases. Reads ./tests/ directory, runs cleanup, wallet setup (if Web3), executes tests, and generates report.
Analyze ANY web project - detect if Web3 DApp, research dependencies via WebSearch, understand business functions from code AND UI screenshots, generate test requirements.
Connect wallet to Web3 DApp - navigate to DApp, click Connect Wallet, approve in MetaMask popup, verify connection. Can be used as a test case or as a precondition for other tests.
Clean up test sessions - kill browsers, stop dev servers, free ports, and optionally remove test data. Use this BEFORE starting new tests or AFTER completing tests.
Examines git diffs between commits or branches with intelligent analysis. Provides unified diff format with comprehensive summaries including file statistics, rename detection, and merge commit handling. Output...
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyze...
嚴謹 TDD 流程:讀取 gherkin(e2e/specs/*.feature)→ Plan mode 規劃測試 → 建立 Git 分支 → 啟動 Wallaby → Red-Green-Refactor 迴圈 → 重構(JetBrains MCP: get_file_problems, reformat_file, ESLint)→ commit(commitl...
引導新功能開發啟動:需求確認、技術設計、分支建立、Gherkin 模板產生。觸發:「開始新功能」、「啟動功能開發」、「feature start」。輸出:feature branch、gherkin 模板、TODO 清單。(project)
Manage AI training data, monitor content freshness, detect repetition, and update training samples for continuous learning. Use when managing training data, checking content quality, updating AI models, or prev...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.