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Found 349 Skills
OSINT-based technology stack identification. Discovers company tech stacks using passive reconnaissance across 17 intelligence domains. Given a company name (and optional domain hint), infers frontend, backend, infrastructure, and security technologies using publicly available signals.
Decomposes a spec or architecture into buildable tasks with acceptance criteria, dependencies, and implementation order for AI agents or engineers. Produces `.agents/tasks.md`. Not for clarifying unclear requirements (use discover) or designing architecture (use system-architecture). For code quality checks after building, see review-chain. For packaging and PRs, see ship.
Generate and critically evaluate grounded ideas about a topic. Use when asking what to improve, requesting idea generation, exploring surprising directions, or wanting the AI to proactively suggest strong options before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on X', 'surprise me', 'what would you change', or any request for AI-generated suggestions rather than refining the user's own idea.
Orchestrates multi-advisor council debates on high-impact architecture, technology, or product decisions. Dispatches 3-5 domain archetype subagents (pragmatic-engineer, architect-advisor, security-advocate, product-mind, devils-advocate, the-thinker) through opening statements, tensions, position evolution, and synthesis phases. Preserves dissent and delivers actionable recommendations with captured risks. Use when evaluating trade-offs, stress-testing a PRD or tech spec, resolving dilemmas with multiple viable options, or when a decision needs diverse expert perspectives. Don't use for simple yes/no questions, factual lookups, creative brainstorming without tradeoffs, or tasks where a single expert perspective suffices.
Run a structured multi-perspective council on a hard decision, design choice, debugging question, strategy problem, or tradeoff. Use when the user wants multiple viewpoints, explicit cross-examination, and a compact final verdict.
This skill should be used when the user wants to implement features or fix bugs using test-driven development. Enforces the RED-GREEN-REFACTOR cycle with vertical slicing, context isolation between test writing and implementation, human checkpoints, and auto-test feedback loops. Uses multi-agent orchestration with the Task tool for architecturally enforced context isolation. Supports Jest, Vitest, pytest, Go test, cargo test, PHPUnit, and RSpec.
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.
Spawn and manage parallel AI coding agents via tmux. Use when you need to orchestrate workers, delegate sub-tasks, run multi-agent improvement loops, or manage agent lifecycles with orca CLI commands like spawn, list, kill, steer, logs, and daemon.
Build software products autonomously via GSD headless mode. Handles the full lifecycle: write a spec, launch a build, poll for completion, handle blockers, track costs, and verify the result. Use when asked to "build something", "create a project", "run gsd", "check build status", or any task that requires autonomous software development via subprocess.
Use the Orca CLI to coordinate multiple coding agents via inter-agent messaging, task DAGs, dispatch with preamble injection, decision gates, and coordinator loops. Use when an agent needs to send or check inter-agent messages; create, dispatch, or track orchestration tasks; coordinate multi-agent workflows; or act as a coordinator dispatching work across terminals. Triggers include "orchestrate agents", "dispatch task", "send message to agent", "check inbox", "coordinate agents", "multi-agent", "create task DAG", "worker_done", "escalation", or any task involving inter-agent coordination through Orca.
Execute from requirement analysis to frontend design document creation
PeachSolution 신규 모듈 개발을 조율하는 통합 팀 스킬. 준비된 DB 스키마와 Spec, ui-proto 기반 표준 모드 + Spec만 모드 + 자연어 prompt 모드를 지원. "팀으로 만들어줘", "풀스택 개발", "팀 개발", "백엔드+UI 전체 생성", "버그 수정해줘", "이 화면에 X 추가해줘", "API와 화면 같이 만들어줘", "백엔드만 만들어줘", "API만 만들어줘", "UI만 추가" 키워드로 트리거. mode=backend(API+Store) | ui(UI만) | fullstack(전체) 지원하며, mode/proto 없이 자연어 입력만으로도 즉흥적 버그 수정·기능 추가 가능. 대규모 작업은 기능 큐와 Contract Gate로 1차 완성도를 높이는 방향을 따른다. peach-team-e2e와 함께 하나의 개발-검증 납품 흐름을 이루되, E2E 검증 독립성은 유지한다. 팀 실행 방식은 요청 범위와 런타임 도구 가용성을 분석해 single-agent / role-queue / agent-team 중 선택한다. 기존 팀 개발 스킬의 개발 조율 역할을 대체하며, DB 생성은 peach-gen-db 선행 단계로 분리한다.