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Found 1,573 Skills
Expert skill for building AI systems with Weft, a Rust-based programming language where LLMs, humans, APIs, and infrastructure are first-class primitives with typed connections and durable execution.
Karpathy LLM Wiki 패턴 기반 지식 관리 스킬. 코드 프로젝트와 옵시디언 노트 모두 지원. Raw Source(코드·문서)를 읽어 docs/wiki/에 누적형 지식베이스를 구축·유지한다. "wiki", "위키", "ingest", "인제스트", "wiki 점검", "wiki lint", "wiki 업데이트", "문서화해줘", "아키텍처 설명해줘", "어떻게 동작해?" 키워드로 트리거. qmd 검색 도구와 연동하여 토큰 절약 + 높은 검색 정확도 제공.
Use this skill whenever an LLM agent needs to search, browse, or download 3D models from Poly Pizza (poly.pizza) using their REST API. Triggers on any task involving: finding free low-poly 3D models, searching the Poly Pizza catalogue, fetching model metadata or download URLs, retrieving popular models, or downloading .glb files from Poly Pizza. Use this skill proactively whenever the agent needs to obtain 3D assets programmatically, even if the user just says "find me a 3D model of X" without mentioning Poly Pizza by name.
[production-grade] Implements autonomous testing and self-healing workflow. After code generation, automatically runs tests (unit, integration, visual, E2E), detects bugs, attempts auto-fix, and continues development. Requires: Vitest, Playwright, Applitools, LLM access.
This skill should be used when implementing, consuming, or debugging an Open Responses-compliant API — the open standard for multi-provider LLM interoperability. Covers protocol, items, state machines, streaming events, tools, the agentic loop pattern, and extensions. Triggers on: Open Responses, open-responses, /v1/responses endpoint, multi-provider LLM API, Open Responses compliance.
Use when revising existing wiki pages because knowledge has changed, a new piece of information updates or contradicts existing content, or the user wants to directly edit wiki content with LLM assistance.
Analyzes images using a vision-capable LLM (Optic). Can read workspace images, URLs, base64 data, or previously generated images by ID.
Extract text from PDFs as structured, semantic Markdown. Use when converting a PDF to Markdown, extracting text from a PDF, processing one or more PDFs into Markdown output, reading PDF contents for analysis, ingesting documents for RAG pipelines, preparing PDFs for LLM context, or any task where PDF text needs to be in a machine-readable format. ALWAYS use this skill when the user has a PDF and needs its content as text or Markdown — even if they don't explicitly say "convert to markdown".
Read every docs/benchmarks/runs/*.json and surface drift in win rate, latency, escalation rate, and LLM-baseline cost over time
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.
Browser automation MCP server using Playwright's accessibility tree for LLM-friendly web interaction
Structured learning roadmap for AI Agent development from LLM basics to multi-agent systems (bilingual Chinese/English)