探索我们完整的 Claude 技能集合,扩展 AI 代理的能力。
Generates comprehensive health reports and risk assessments for software initiatives by analyzing documentation, Jira tickets, and code repositories.
Logs Claude Code work sessions directly into LogSeq journals with time-stamped summaries and automated tagging.
Optimizes SQL query performance through systematic indexing, EXPLAIN plan analysis, and efficient query refactoring patterns.
Streamlines rapid TDD iteration cycles by synchronizing Jira context, codebase exploration, and automated branch setup.
Integrates external AI models like Grok, ChatGPT, and Gemini to provide multi-perspective code reviews and architectural second opinions.
Streamlines GitLab CI configuration by applying best practices for job dependencies, stages, and pipeline structure.
Guides developers through the AI-Driven Development Lifecycle (AI-DLC) methodology and plugin ecosystem for AI-native software engineering.
Lists and organizes available GitLab CI pipeline standards and best practices for quick reference and navigation.
Generates a comprehensive preview of file operations, CI/CD pipeline changes, and infrastructure configurations before executing a trunk-based migration.
Standardizes the creation and maintenance of human-readable changelogs following professional software documentation best practices.
Audits GitLab CI pipeline configurations for compliance with industry best practices and organizational standards.
Automates and guides the transition of .NET services from branch-based GitLab Flow to modern trunk-based development.
Provides migration pathways and guidance for transitioning from the legacy planning plugin to the enhanced AI-DLC methodology tools.
Manages chains of dependent Git branches to split large features into small, reviewable pull requests.
Automates the creation of detailed GitLab merge requests by analyzing branch commits and code differences.
Automates the discovery and configuration of .NET repositories for trunk-based deployment migrations by scanning codebases and infrastructure manifests.
Generates a real-time health and status dashboard for all Product Requirements Documents in your project.
Provides real-time guidance and best practices for Ruby, Rails, Python, and SQL implementation to ensure code quality and prevent common bugs.
Automates the creation of structured release notes by analyzing git history, GitLab merge requests, and Jira tickets.
Bridges the gap between planning and implementation by generating domain models, logical architectures, and Architecture Decision Records (ADRs).
Performs senior-level peer reviews of GitLab merge requests and AI-DLC documentation artifacts with automated confidence scoring.
Generates comprehensive, production-ready .NET unit tests using NUnit, FakeItEasy, and FakeXrmEasy for standard C# projects and Dataverse plugins.
Drafts and refines structured project intent documentation in Confluence with built-in risk assessment and stakeholder validation.
Displays human-readable summaries of GitLab CI pipeline best practices and standards directly in your terminal.
Automates post-migration workflows for trunk-based development, including deployment monitoring, repository cleanup, and security hardening.
Decomposes approved development intents into structured Units and Tasks within Confluence for collaborative architectural review.
Validates trunk-based migrations by verifying Kustomize builds, GitLab CI/CD pipeline components, and Kubernetes configurations.
Diagnoses Sentry errors by analyzing codebase patterns and recommending specific diagnostic or corrective scripts from GitLab repositories.
Automates complex browser interactions for web testing, data extraction, and UI manipulation using simple terminal commands.
Implements efficient similarity search and vector database patterns for semantic retrieval and RAG systems.
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