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Found 787 Skills
Run /check-posthog, then fix the highest priority PostHog integration issues. Focuses on one issue at a time for safe, incremental fixes. Invoke for: PostHog not working, events not sending, analytics broken.
Session mode: act as orchestrator brain only. Research and implementation go to cheaper-model subagents; the orchestrator scopes, briefs, verifies, and judges. User-invoked with the task as the argument.
Refactor CLAUDE.md files to follow progressive disclosure principles. Use when CLAUDE.md is too long or disorganized.
An Agent dedicated to brainstorming and finalizing specifications. Finalize a single, implementable and testable Spec.md.
Iterative execution methodology. Small steps, verify each, adapt based on results.
Bootstrap agentic development environment from agent.toml manifest
Chain-of-thought reasoning, self-reflection, and systematic problem-solving patterns for AI agents. Use before any complex task to ensure logical and accurate solutions.
Use when building anything non-trivial. Enforces a spec → plan → execute → verify loop that prevents "looks right" failures. Creates spec.md, todo.md, and decisions.md before writing code.
Set up API integration with configuration and helper scripts
6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks. Optimized for exploration and understanding, not implementation. Includes parallel agent deployment for efficient deep dives and automatic knowledge capture to prevent repeat investigations.
Comprehensive Go backend code review with optional parallel agents
Use this when the user explicitly requests to "verify/optimize in-text citations of the `{topic}_review.tex` review" or to "run check-review-alignment". Use the host AI's semantic understanding to verify each citation against the literature content one by one. **Only when fatal citation errors are found**, make minimal rewrites to the "sentences containing citations", and reuse the rendering script of `systematic-literature-review` to output PDF/Word (the script does not directly call the LLM API locally). Core principle: **Do not modify for the sake of modifying**. When it is uncertain whether it is a fatal error, keep the original content and issue a warning in the report. ⚠️ Not applicable in the following cases: - The user only wants to generate the main body of a systematic review (should use systematic-literature-review) - The user only wants to add/verify BibTeX entries (should use a dedicated bib management process)