Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
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Delegates tasks to Meta's Muse Code CLI (muse) via delegation-core. Use when delegation-core selects Muse or repository-scale work needs a 1M-token context.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Muse Code is Meta's terminal coding agent, released August 2026 and built on Muse Spark 1.2. It runs either as an interactive TUI or as a one-shot headless command, and the headless form is what delegation uses.
The binary is muse. Meta publishes no npm or PyPI package for it:
the documented install is a script served from Meta's own domain.
delegation-core selected muse for the taskmuse exec is designed for
CIMETA_API_KEY is unset and the run cannot be interactive--model flag
for exec, so the CLI default standsexeccurl -fsSL https://dev.meta.ai/install.sh | sh
This pipes a remote script into a shell. Read https://dev.meta.ai/docs/muse-code before running it. The guided installer offers the same command and shows its source first:
make -C plugins/conjure delegate-setup
Meta documents the environment variable as the CI path:
export META_API_KEY="<your-key>"
muse exec "Run the test suite and summarize failures."
A bare muse prompts for browser sign-in on first run, which is not
usable unattended. There is no muse auth status command, so the
service declares an empty auth probe and verification checks
META_API_KEY instead.
uv run python scripts/delegation_executor.py muse "Summarize this module" \
--files src/
make -C plugins/conjure delegate-muse PROMPT='Explain this design'
muse exec "Explain the retry logic in this package"
muse declares the strengths code_execution and large_context,
and ranks behind gemini, qwen, minimax and glm in the candidate order.
It declares no model ids, so smart_delegate leaves model selection
to the CLI rather than passing a flag Meta does not document.
| Property | Value |
|---|---|
| Binary | muse |
| Headless form | muse exec <prompt> |
| Prompt delivery | positional, no flag |
| Version probe | muse --version |
| Auth probe | none published |
| Auth | META_API_KEY |
| File context | inlined, no @path syntax |
The prompt is positional. A command ending in a flag would consume the
prompt as that flag's value, which is why the service config sets
prompt_flag=None and the War Room expert's command ends at
muse exec.
Two claims circulating in third-party guides are not in Meta's own
documentation and are not relied on here: a --json flag streaming
JSONL events to stdout, and muse auth set --api-key-stdin. The
confirmed JSONL reference is to on-disk session logs. Treat both as
unverified until Meta documents them.
muse resolves on PATH and muse --version answersMETA_API_KEY is set, or the operator accepted an interactive
sign-inmuse exec <prompt> with the prompt as the
final argument and no prompt flag before it@path referencesdelegations/muse/YYYYMMDD_HHMMSS.mddelegation-core selected muse, not by
default아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
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Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
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Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
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Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
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