Loading...
Loading...
Found 1,335 Skills
Iterate on RAG systems with structured evals instead of eyeballing. This skill should be used when the user is tuning a RAG pipeline — changing retrieval prompts, swapping models, adjusting chunking, or debugging poor answers — and wants a cheap, ranked set of experiments with cost tracking and structured feedback on the stack. Also use when the user asks "how do I know if my RAG is working?", "this RAG eval is burning money", or "what should I try next on retrieval?".
Use when crawling web pages, extracting markdown content, or scraping website data with intelligent chunking and skeleton planning. Use when the user provides a URL or link to fetch or crawl.
Manage shell hooks — user scripts that run at agent lifecycle points to block, rewrite, or warn on actions, via the /hooks command.
Give every AI agent its own computer: a persistent workspace with a filesystem, processes, shells, networking, and agent sessions on a lightweight in-process OS.
Interact with Litefuse and access its documentation. Use when needing to (1) query or modify Litefuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Litefuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any Litefuse feature works. This skill covers CLI-based API access (via npx) and multiple documentation retrieval methods.
Structured producer who turns research insights into production-ready slide deck outlines and scripts. Triggers: 'create slides', 'write webinar script', 'build slide deck', 'webinar outline', 'produce webinar', or when user asks for the Producer.
Rewrite text to remove AI tells. Use when editing or reviewing writing that sounds like a chatbot wrote it. Detects and replaces inflated significance, rule-of-three, em dash overuse, AI vocabulary, condescending openers, reader-lecturing, signposting, and other tells.
Build modular Agentic RAG systems with LangGraph, featuring hierarchical indexing, conversation memory, and multi-agent query processing
AI-automated penetration testing and general problem-solving system that achieved unique AK (All Killed) in Tencent Cloud Hackathon intelligent penetration challenge
Index and search Claude Code sessions using semantic embeddings (Gemini). Find past sessions by topic, relaunch the best match. Triggers on "find session", "which session did I", "relaunch the session where", "session about X".
Help users define AI product strategy. Use when someone is building an AI product, deciding where to apply AI in their product, planning an AI roadmap, evaluating build vs buy for AI capabilities, or figuring out how to integrate AI into existing products.
Merges valuable content into permanent documentation, then deletes source files. Use when you have untracked *_REPORT.md or *_ANALYSIS.md files, git status shows markdown artifacts that shouldn't be committed, preparing PR and need to clean up working artifacts, preserving insights from code reviews. Do not use when files are already in docs/ or skills/ locations. DO NOT use when: files are intentionally temporary scratch notes. DO NOT use when: source files have no extractable value.