sentry-setup-ai-monitoring
Setup Sentry AI Agent Monitoring in any project. Use this when asked to add AI monitoring, track LLM calls, monitor AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI. Automatically dete...
Browse published AI skills maintained by troykelly. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
128Repository stars across indexed skills
640Repository forks
61Average repository stars per indexed skill
5Repository stars may repeat across skills from the same repository.
Setup Sentry AI Agent Monitoring in any project. Use this when asked to add AI monitoring, track LLM calls, monitor AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI. Automatically dete...
Use when user requests autonomous operation across multiple issues. Orchestrates parallel workers, monitors progress, handles SLEEP/WAKE cycles, and works until scope is complete without user intervention.
Use when the user wants to create or refine Codex skills, improve skill descriptions, organize skill resources, or follow Codex skill best practices.
Use when encountering merge conflicts - handle conflicts cleanly, verify resolution, and maintain code integrity
Use when writing code, documentation, or comments - always use accessible and respectful terminology
Use when writing code in typed languages - enforces full typing with no any/unknown/untyped escapes, even if it requires extra time
Defines context handover format when workers hit turn limit. Posts structured handover to GitHub issue comments enabling replacement workers to continue seamlessly.
MANDATORY for all work - the project board is THE source of truth. This skill provides verification functions and gates that other skills MUST call. No work proceeds without project board compliance.
Use before starting ANY work - hard gate ensuring a GitHub issue exists, creating one if needed through user questioning
Use before merging PR - final gate ensuring all tests pass, review complete, CI green, and acceptance criteria verified
Use when writing code - ensure complete JSDoc, docstrings, and inline comments assuming documentation will be generated from code
Use when a review finding cannot be fixed in current PR - creates properly documented tracking issue with full context, linked to parent, following full issue-driven-development process
Use when asked to trace existing codepaths or explicitly asked to run the code-explorer subagent.
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 avoid...
Use when explicitly asked to run the code-reviewer subagent or when another skill requires the code-reviewer agent card.
Use when asked to evaluate type design/invariants or explicitly asked to run the type-design-analyzer subagent.
Use for LARGE work requiring feature-level grouping. Creates epic tracking issues, manages related issues under a common label, tracks epic progress, and coordinates with milestones.
Use after creating PR - monitor CI pipeline, resolve failures cyclically until green or issue is identified as unresolvable
Use at the beginning of every work session - establishes context by checking GitHub project state, reading memory, verifying environment, and orienting before starting work
Use before any code changes - hard gate ensuring work never happens on main branch, with proper feature branch creation from correct base
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
Use when asked to review code comments for accuracy/quality or explicitly asked to run the comment-analyzer subagent.
Use when an issue is too large for a single task - breaks into linked sub-issues with full documentation, ensuring manageable work units
Use when asked to evaluate PR test coverage or explicitly asked to run the pr-test-analyzer subagent.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.