Writing Hookify Rules
Create and configure Hookify rules to watch for specific patterns in files, bash commands, or user prompts.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
315 skills found
Create and configure Hookify rules to watch for specific patterns in files, bash commands, or user prompts.
Automate GitHub issue triage by analyzing reports against the codebase, verifying technical claims, and providing expert-driven responses to resolve invalid issues.
A secure Git commit workflow agent that prevents accidental mass commits and promotes surgical, file-specific staging and semantic commits.
Automated Vercel production deployment agent that fetches logs via MCP, identifies build errors, applies fixes, and retries until success.
Defense-in-depth protection for Claude Code. Manage security hooks to block dangerous commands, enforce file access controls, and protect sensitive paths across global or project-specific scopes.
Neuropixels neural recording analysis toolkit. Provides end-to-end pipelines for SpikeGLX/OpenEphys data, Kilosort4 spike sorting, motion correction, quality metrics, and AI-assisted curation.
Automated toolkit for creating, maintaining, and enhancing CLAUDE.md files to ensure your project's AI-assisted development guidelines are always accurate, modular, and best-practice compliant.
Remove AI-generated patterns and inject natural human voice into your writing. Fixes robotic phrasing, overuse of AI vocabulary, and sterile structure to make text sound authentic.
A stage-driven AI writing agent for structured, repeatable, and reversible long-form content production with human-in-the-loop workflows.
Bayesian modeling and probabilistic programming with PyMC. Build hierarchical models, perform MCMC sampling (NUTS), variational inference, and conduct rigorous model comparison using LOO and WAIC.
Systematic Kubernetes troubleshooting, pod diagnostics, cluster health monitoring, and incident response playbooks.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.