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Claude Code 스킬로 외부 OpenAI 호환 채팅 엔드포인트에 작업을 위임하고 먼저 기능을 탐색한 뒤 오류 가능성을 인식하며 위임합니다
A Claude Code skill that lets you delegate tasks to external OpenAI-compatible chat endpoints. Probe capabilities first, then delegate with awareness of what can go wrong.
스킬Shell · PyretGitHub @caasi직접 설치운영자 미확인
써 보셨어요? 한 번만 눌러 주세요. 로그인은 필요 없어요.
아직 감지된 업데이트가 없습니다. GitHub 릴리스가 나오면 여기에 보입니다.
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
설치형 프로젝트는 배포 도메인 없이도 확인할 수 있습니다. 개인 저장소는 GitHub 로그인으로, 조직 저장소는 위의 저장소 확인 파일로 직접 확인해 주세요.
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
A Claude Code plugin marketplace by caasi.
Delegate tasks to external OpenAI-compatible chat endpoints with capability probing, delegation patterns, and prompt injection awareness.
See plugins/chat-subagent/skills/chat-subagent/README.md for full documentation.
Describe multi-step agent workflows using an Arrow-style DSL and validate them structurally with the ocaml-compose-dsl binary. The DSL is a planning language — the agent expands it into concrete tool calls.
See plugins/compose/skills/compose/README.md for full documentation.README 전문 보기 ↗A Claude Code plugin marketplace by caasi.
Describe multi-step agent workflows using an Arrow-style DSL and validate them structurally with the ocaml-compose-dsl binary. The DSL is a planning language — the agent expands it into concrete tool calls.
See plugins/compose/skills/compose/README.md for full documentation.
Natural language constraints → deterministic test artifacts. Write constraints in structured Markdown (constraints/*.md with Given/When/Then/Unless/Examples/Properties), generate unit tests / PBT / mutation tests, and enforce with a 4-layer deterministic pipeline.
Explore an unfamiliar codebase together with the agent, one step at a time. The agent follows one value through the code, reads the types along its path, marks each finding [read] or [spike], and ends each answer with where to read next.
See plugins/dataflow/skills/dataflow/README.md for full documentation.
Reflect on human-AI stewardship through Socratic dialogue. A mirror, not a checklist — rooted in Audrey Tang's Humane Intelligence framework and Civic AI 6-Pack of Care.
See plugins/kami/skills/kami/README.md for full documentation.
FP-thinking review and refactor for pre-RSC React (classes, hooks, Redux/MobX/observable, Reselect, Immer). Ships only architectural rules where neither TypeScript nor eslint-plugin-react-hooks already enforces the principle. Five active categories: state architecture (model-), effects (effect-), composition (compose-), render purity (purity-), and hook applicability (hooks-). Two categories (immutable-, message-) defer to existing tooling. One slash command: /old-react [review|refactor] [path].
See plugins/old-react/skills/old-react/README.md and SKILL.md for the canonical rule list.
Assisted (not autonomous) multi-reviewer convergence loop for any change — code or design artifacts. Local reviewers answer blind and in parallel on the same unfixed diff (a Claude subagent always, plus any models/CLIs you enrol per host — Codex via headless codex exec when present), then GitHub Copilot for PR targets. The verdict names which reviewers actually ran; heterogeneity is a bonus, not a gate, and same-family review is never treated as a downgrade. Classifies comments into tiers, auto-fixes the mechanical ones, pauses for your judgment on the architectural ones, and never merges on its own. It publishes its stop shape before round 1 and holds to it, and a T3 that comes back after a fix makes that round's message a question about the whole change's direction as well as asking for the item's own fix. How a finding is settled follows who reads the artifact: a behaviour claim about a runtime prompt is settled by five independent simulation runs, never by a string comparison. Two slash commands: /review-loop [PR# | branch | blank] and /review-loop:init (enrol the roster for this host).
See plugins/review-loop/skills/review-loop/README.md for full documentation.
A git-native skill for unattended work preparation and human–agent convergence. Using git's DAG as the coordination substrate, an agent prepares engineering work privately on git branches (often while you are away), records evidence in committed .tsugu/ notes, and packages a convergence packet; when you return you converge — review the prepared evidence, decide together what becomes public, and complete the disposition in the same session (cut a handoff branch / open a PR, human-gated — the merge lands when you approve it). Three routines: init (set up or migrate the repo's .tsugu/ workspace + policy.md), prepare (private git work on the configured work prefixes — defaults prepare/* investigate/* review/* — + tests + evidence while you are absent), converge (present the packet, decide with you, and complete the disposition + a read-only morning status view). State is derived from refs and the DAG, not stored in status fields, so merge commits are recommended; .tsugu/ MAY land on the mainline by default (public-branch-tsugu: include|exclude). Never auto-merges; light and script-free; invokes no user-installed skill by default (per-repo policy.md may opt-in). Three slash commands: /tsugu:init, /tsugu:prepare, /tsugu:converge.
See plugins/tsugu/skills/tsugu/README.md for full documentation.
claude plugin marketplace add caasi/dong3
MIT