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Found 4,154 Skills
Analyze GitHub issues by link or issue number. Use when a user says "analyse issue"/"analyze issue" or provides a GitHub issue URL/number and asks to fetch the issue content, verify it matches the current repo, and inspect local code to confirm the problem.
This skill should be used when performing a code review on local changes on the current branch compared to the main branch. It uses multiple parallel agents to check for bugs, CLAUDE.md compliance, git history context, previous PR comments, and code comment adherence, then scores and filters findings by confidence level.
CX Workflow - Configuration Management. View and modify configuration fields in config.json, such as developer_id, github_sync mode, code review toggle, agent team mode, auto-formatting, etc. Trigger words: config, settings, modify config, change mode. Only execute when the user explicitly calls /cx-config. Do not trigger automatically.
Bitbucket Git repository hosting with Pipelines. Use for Atlassian teams.
This skill should be used when the user asks to "create a pull request", "create PR", "open PR", "update a pull request", "update PR", "create an issue", "file an issue", "create a GitHub issue", "create a Claude Code issue", "report a bug in Claude Code", "create a Codex issue", "report a bug in Codex CLI", "create a Sablier issue", "file an issue in sablier-labs", "create a discussion", "start a GitHub discussion", or mentions OSS contribution workflows.
Terminal session manager for AI coding agents. Use when user mentions "agent-deck", "session", "sub-agent", "MCP attach", "git worktree", or needs to (1) create/start/stop/restart/fork sessions, (2) attach/detach MCPs, (3) manage groups/profiles, (4) get session output, (5) configure agent-deck, (6) troubleshoot issues, (7) launch sub-agents, or (8) create/manage worktree sessions. Covers CLI commands, TUI shortcuts, config.toml options, and automation.
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. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Automatically discover life science APIs online, create ToolUniverse tools, validate them, and prepare integration PRs. Performs gap analysis to identify missing tool categories, web searches for APIs, automated tool creation using devtu-create-tool patterns, validation with devtu-fix-tool, and git workflow management. Use when expanding ToolUniverse coverage, adding new API integrations, or systematically discovering scientific resources.
Runs an autonomous development loop with research and implementation modes. Use when orchestrating iterative research and implementation cycles with dots-based task tracking and git workflow automation.
Run /check-posthog, then create GitHub issues for all findings. Each finding becomes a separate, actionable issue with clear acceptance criteria. Invoke for: PostHog audit to issues, analytics backlog creation.
Capture AI agent sessions in your git workflow. Use for setup, rewinding to checkpoints, exploring session history, and troubleshooting.
Monitors awesome-copilot releases for drift against the amplihack integration. Checks latest commits on github/awesome-copilot via the GitHub API and reports whether the local integration is current or has drifted behind upstream changes. Use when auditing integration freshness or before updating awesome-copilot features.