codeql
Perform deep security analysis on codebases using CodeQL for interprocedural data flow, taint tracking, and automated vulnerability detection across multiple languages.
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176 skills found
Perform deep security analysis on codebases using CodeQL for interprocedural data flow, taint tracking, and automated vulnerability detection across multiple languages.
Standardize code documentation: automate READMEs, API references, JSDoc/TSDoc, and Architecture Decision Records (ADRs) to maintain clean, professional technical guides.
AI-native product management tool for startups. Features automated competitor research, gap analysis using the WINNING filter, PRD generation, and GitHub Issues integration for prioritized, signal-based roadmap planning.
Manage agent skills with the ClawdHub CLI: search, install, update, and publish skills directly from clawdhub.com for your local AI assistant.
Implement Extreme Programming (XP) practices including TDD, pair programming, and continuous integration to enhance team collaboration and technical excellence in software engineering.
Monitor and manage margin-living strategy by tracking balances, interest costs, and coverage ratios. Provides automated scaling recommendations and safety alerts based on portfolio-to-margin thresholds.
Production-ready Scrum Master assistant for sprint management, capacity planning, and real-time team analytics.
A deep analysis tool for A-share markets generating interactive, FT-style HTML daily reports using multi-agent parallel architecture, AkShare data, and Tavily news.
End-to-end GitHub repository maintenance agent. Automates triage, PR review, issue analysis, and maintenance reporting to ensure long-term repository health, stability, and growth.
Manage automatic model routing for Higress AI Gateway via CLI. Configure triggers for intelligent model selection based on request content.
Automates the release process by creating a pull request from main to production with automated semantic versioning calculations.
A structured decision-making tool that applies RICE, MoSCoW, Kano, and value-effort frameworks to prioritize software features, roadmap items, and build-vs-defer decisions with data-driven objectivity.