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Found 1,058 Skills
Guide for creating high-quality, user-friendly diagnostics in Biome. Use when implementing error messages, warnings, and code frame displays. Examples:<example>User needs to create a diagnostic for a lint rule</example><example>User wants to add helpful advice to error messages</example><example>User is improving diagnostic quality</example>
Step-by-step guide for creating and implementing lint rules in Biome's analyzer. Use when implementing rules like noVar, useConst, or any custom lint/assist rule. Examples:<example>User wants to create a rule that detects unused variables</example><example>User needs to add code actions to fix diagnostic issues</example><example>User is implementing semantic analysis for binding references</example>
Guide for working with Biome's module graph and type inference system. Use when implementing type-aware lint rules or working on TypeScript support. Examples:<example>User needs to understand type resolution for a lint rule</example><example>User is working on the module graph infrastructure</example><example>User wants to implement type inference for a new feature</example>
Run holistic pedagogical review on lecture slides. Checks narrative arc, student prerequisites, worked examples, notation clarity, and deck pacing.
Generate concise Git commit messages in imperative mood. Analyzes staged changes first; if none, examines unstaged and untracked files. Use when the user asks to create, write, draft, make, or generate a commit message.
Use this skill when crafting, reviewing, or improving prompts for LLM pipelines — including task prompts, system prompts, and LLM-as-Judge prompts. Triggers include: requests to write or refine a prompt, diagnose why an LLM produces inconsistent or incorrect outputs, bridge the gap between intent and model behavior, reduce ambiguity in instructions, add few-shot examples, structure complex prompts, or improve output formatting. Also use when the user needs help distinguishing specification failures (unclear instructions) from generalization failures (model limitations), or when iterating on prompts based on observed failure modes. Do NOT use for general coding tasks, document creation, or non-LLM writing.
Full DeepRead API reference. All endpoints, auth, request/response formats, blueprints, webhooks, error handling, and code examples.
Guide for adding new environment variables to the codebase. Ensures env.ts schemas include descriptions and .env.example is kept in sync. Triggers on: add env variable, new environment variable, env.ts change, add config variable, INKEEP_, adding to .env.
Best practices, patterns, and examples for building goal-driven agents. Includes client-facing interaction, feedback edges, judge patterns, fan-out/fan-in, context management, and anti-patterns.
Research a UI design aesthetic and produce exhaustive, implementation-ready design guidelines for coding agents. Use when the user names an aesthetic (brutalist, glassmorphism, retro-futuristic, Swiss modernist, Apple HIG, neumorphism, minimalism, cyberpunk, Material Design, art deco, vaporwave, etc.) and wants a complete style guide with exact CSS values, color palettes, component states, animations, and typography — detailed enough for a coding agent to faithfully implement the aesthetic with zero ambiguity.
Create a minimal working Evernote example. Use when starting a new Evernote integration, testing your setup, or learning basic Evernote API patterns. Trigger with phrases like "evernote hello world", "evernote example", "evernote quick start", "simple evernote code", "create first note".
Enrich contact, company, and influencer data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Scraping full LinkedIn profiles (experience, education, skills) - Searching for people or companies by criteria - Bulk enrichment operations (up to 10 at a time) - Verifying email deliverability before outreach - Enriching influencer/creator profiles across social platforms TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" - "verify email", "check email", "is this email valid" - "influencer", "creator", "influencer contact", "influencer marketing" ALWAYS use `npx agentcash fetch` for stableenrich.dev endpoints - never curl or WebFetch. Returns structured JSON data, not web page HTML. IMPORTANT: Use exact endpoint paths from the Quick Reference table below. All paths include a provider prefix (`https://stableenrich.dev/api/apollo/...`, `https://stableenrich.dev/api/clado/...`, etc.).