claude-forge

Use *before* starting work in a domain you don't know well, to surface the "unknown unknowns" — the things you don't even know to ask about — and learn just enough to prompt and decide well. Implements the "blind spot pass" pattern from Anthropic's Fable "finding your unknowns" field guide. Triggers when you say "I'm new to this", "I don't know what to ask", "teach me before we start", "blind spot pass", "unknown unknowns", "find my unknowns", or the Korean "내가 뭘 모르는지 알려줘" / "이 분야 처음인데" / "먼저 가르쳐줘" / "블라인드 스팟", or when you hand off a task while admitting you're a non-expert in that field (color grading, video editing, legal, tax, finance, design, an unfamiliar codebase, etc.). Do NOT use for simple factual questions, domains you already know, or directly-actionable work — answer those directly or route to planner / architect.

Turn a one-line description of a repetitive task into a reusable, self-guarding slash command. loop-forge diagnoses the task into one of 5 loop shapes (Batch / Pipeline / Refine / Watch / Explore), interviews for the blanks, and auto-injects two safety devices the user didn't know they needed — an independent verifier (maker ≠ checker) and a hardstop (a budget/count/cooldown ceiling) — then previews the result and stamps it as a `/command` they can run forever. Use when the user says "/loop", "/loop-forge", "/make-it-loop", "automate this", "make this repeatable", "turn this into a command", "do this for all 100 items", "do X every time Y happens", "generate several and pick the best", or otherwise wants to capture a recurring task as a reusable slash command instead of re-typing the prompt by hand. Works in any language: it interviews the user and writes the stamped command in the user's own language. Non-goal — it does not schedule unattended runs (launchd/cron) or publish externally on its own; it stamps t

Use when detecting and running project build systems automatically. Supports npm/yarn/pnpm/pip/poetry/gradle/maven/cargo/go/make. Triggers on build, test run, project setup, package manager detection.

Use when starting Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev workflow.

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles

Use when searching, installing, or improving AI skills and prompts via prompts.chat or skills.sh. Triggers on skill search, prompt lookup, install skill, improve prompt, prompts.chat.

Use when security verification is needed - pre-commit security checks, vulnerability scanning, STRIDE threat analysis. Integrates with /handoff-verify --security and /commit-push-pr. CWE Top 25 based.

Use when wrapping up a session before ending. 4 parallel subagents detect doc updates, repeated patterns, learning points, and follow-ups, then a verifier deduplicates and presents choices. Triggers on /session-wrap, session wrap, session cleanup, end of session.

Use when orchestrating Agent Teams for parallel development - team composition, task distribution, dependency management, and result aggregation. Triggers on /orchestrate, multi-agent coordination, parallel team work, task delegation to teammates.

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

Use when verifying build/test/lint before commit, PR, or completion claims. Runs verification pipeline in fresh subagent context with auto-repair. Triggers on /handoff-verify, pre-commit check, build verification, test validation.

Manage major dependency version upgrades with compatibility analysis, staged rollout, and comprehensive testing. Use when upgrading framework versions, updating major dependencies, or managing breaking changes in libraries.

Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).

세션 변경사항을 분석하여 검증 스킬 누락을 탐지합니다. 기존 스킬을 동적으로 탐색하고, 새 스킬을 생성하거나 기존 스킬을 업데이트한 뒤 프로젝트 CLAUDE.md를 관리합니다.

프로젝트의 모든 verify 스킬을 실행하여 통합 패턴 검증 보고서를 생성합니다. 기능 구현 후, PR 전, 코드 리뷰 시 사용.

Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.

Analyze session work and automatically convert reusable patterns into Claude Code skills. Use when: "세션을 스킬로", "스킬 만들어", "이거 스킬로", "skill factory", "이 작업 자동화해", "스킬 추출", "make this a skill", "extract skill", "convert to skill", "스킬 팩토리", "자동 스킬 생성". Differs from skill-creator (archived) and manage-skills (drift detection): this skill actively analyzes sessions, checks for duplicates, and creates skills via Agent Teams.

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.