Loading...
Loading...
Found 181 Skills
Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.
Orchestrates Story tasks. Prioritizes To Review -> To Rework -> Todo, delegates to ln-401/ln-402/ln-403/ln-404, hands Story quality to ln-500. Metadata-only loading up front.
Hand off to a fresh Claude session. Use when context is full, you've finished a logical chunk of work, or need a fresh perspective. Work continues from hook.
Produce an LLM Build Pack (prompt+tool contract, data/eval plan, architecture+safety, launch checklist). Use for building with LLMs, GPT/Claude apps, prompt engineering, RAG, and tool-using agents.
Use when creating or refining SKILL.md-based skills, or diagnosing weak triggering (under/over-triggering, vague descriptions, bloated context, or missing workflow guidance).
This skill should be used after productive sessions to extract learnings and route them to appropriate Reusable Intelligence Infrastructure (RII) components. Use when corrections were made, format drift was fixed, new patterns emerged, or the user explicitly asks to "harvest learnings" or "capture session intelligence". Transforms one-time fixes into permanent organizational knowledge by implementing updates across multiple files.
Guide for using MassGen to develop and improve itself. This skill should be used when agents need to run MassGen experiments programmatically (using automation mode) OR analyze terminal UI/UX quality (using visual evaluation tools). These are mutually exclusive workflows for different improvement goals.
How to create and maintain agent skills in .agents/skills/. Use when creating a new SKILL.md, writing skill descriptions, choosing frontmatter fields, or deciding what content belongs in a skill vs AGENTS.md. Covers the supported spec fields, description writing, naming conventions, and the relationship between always-loaded AGENTS.md and on-demand skills.
Orchestrator workflow for running ZeroContext Lab (ZCL) attempts/suites with deterministic artifacts, trace-backed evidence, and fast post-mortems (shim support for "agent only types tool name").
Use when research direction needs assessment, critical knowledge gaps must be identified, or priorities must be recommended based on impact, dependencies, and effort (especially at project milestones or when scope questions arise)
주식/ETF 분석 결과 파일 저장 프로토콜. Write 도구 사용 규칙, 저장 경로 컨벤션, 실패 시 응답 형식을 정의합니다.
Create, improve, and audit AI agent skills. Applies 14 proven structural patterns, scores quality with deterministic audit, manages full lifecycle. Use when building, refactoring, or reviewing skills. NOT for agents, MCP servers, or running existing skills.