Loading...
Loading...
Found 4,654 Skills
Analyze collections of user feedback to identify patterns and themes. Use when you have user feedback from multiple sources that needs synthesis.
Select the right Proof of Life (PoL) probe based on hypothesis, risk, and resources. Use this to match the validation method to the real learning goal, not tooling comfort.
TypeScript, React, and JavaScript best practices enforced by Ultracite/Biome.
Use when users want to define, codify, or update their brand identity and connect it to design systems. Produces a self-contained user-level skill at ~/.claude/skills/{brand-slug}/SKILL.md that enforces brand guidelines whenever visual assets or written content are created.
Supabase validation skill. Use when writing, deploying, or modifying any Supabase resource — edge functions, RPC functions, CRUD operations, RLS policies, or schema migrations. Adds mandatory pass/fail verification to every Supabase action before reporting completion.
Multi-AI Parallel Deep Research. Triggered when users need comprehensive research, in-depth study, multi-party comparison, or comprehensive analysis covering multiple dimensions and sources for a certain topic. Suitable for complex topics (technical selection, competitor analysis, industry trends, controversial topics, etc.), not suitable for simple fact queries. Conduct parallel research through multiple AI services, cross-validate, and output a comprehensive report with citations.
Audits and auto-fixes a project's CLAUDE.md against Anthropic best practices. Activates during ship phase — checks conciseness, enforces @import structure for detailed docs, auto-excludes bloat, identifies hook candidates, and auto-fixes structural issues. Flags content questions for developer review.
Better environment variable management for agents and humans with full type safety, CLI-based remote environment synchronization, and environment validation. Use when setting up typed config schemas, validating env variables, or managing remote env vars across Vercel, Netlify, Railway, Cloudflare, and Fly.io with better-env.
Enables interaction with Google NotebookLM for advanced RAG (Retrieval-Augmented Generation) capabilities via the notebooklm-mcp-cli tool. Use when querying project documentation stored in NotebookLM, managing research notebooks and sources, retrieving AI-synthesized information, generating audio podcasts or reports from notebooks, or performing contextual queries against curated knowledge bases. Triggers on "notebooklm", "nlm", "notebook query", "research notebook", "query documentation in notebooklm".
Consult this skill when searching or navigating stored knowledge. Use when searching for stored knowledge, cross-referencing concepts, discovering connections, retrieving from palaces, finding past PR decisions. Do not use when creating new palace structures - use memory-palace-architect. DO NOT use when: processing new external resources - use knowledge-intake.
Audit and maintain README standards across *-skills repositories with a two-pass workflow (audit first, optional bounded fixes second). Use when running Codex App or CLI automations for skills-repo documentation consistency, profile-aware section schemas, command integrity checks, and discoverability baseline enforcement.
Use this when users explicitly request to "generate NSFC schematic diagram/mechanism diagram" or need to convert the research mechanism, algorithm architecture, and module relationships in the proposal into "editable + embeddable" diagrams. By default, editable source files (`.drawio`) and rendered files (`.pdf`/`.svg`/`.png`) are output; when users actively mention the Nano Banana/Gemini image model, you can switch to PNG-only mode. ⚠️ Not applicable scenarios: Users only want to polish the main text (should rewrite text directly), only want to modify the format/size of existing images (should use image processing skills), and have no clear intention of requiring "schematic/mechanism diagram".