muse-delegation
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 …
它会碰到什么
逐条看命中(1 条严重或高危)
- 严重
SKILL.md:72exec-pipe-to-shellcurl -fsSL https://dev.meta.ai/install.sh | sh
这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。
技能内容
Table of Contents
- [Overview](#overview)
- [When To Use](#when-to-use)
- [When NOT To Use](#when-not-to-use)
- [Prerequisites](#prerequisites)
- [Quick Start](#quick-start)
- [Smart Delegation](#smart-delegation)
- [Muse-Specific Details](#muse-specific-details)
- [Exit Criteria](#exit-criteria)
Muse Code Delegation
Overview
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.
When To Use
delegation-coreselectedmusefor the task- Repository-scale reading where Muse Spark 1.2's 1M-token context
helps
- Work that should run unattended, since
muse execis designed for
CI
When NOT To Use
META_API_KEYis unset and the run cannot be interactive- A specific model must be selected. Meta documents no
--modelflag
for exec, so the CLI default stands
- Structured output is required. No output-format flag is documented
for exec
Prerequisites
Installation
curl -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
Authentication
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.
Quick Start
Using the shared delegation executor
uv run python scripts/delegation_executor.py muse "Summarize this module" \
--files src/
Through the Makefile
make -C plugins/conjure delegate-muse PROMPT='Explain this design'
Direct CLI usage
muse exec "Explain the retry logic in this package"
Smart Delegation
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.
Muse-Specific Details
| 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.
Exit Criteria
- [ ]
museresolves on PATH andmuse --versionanswers - [ ]
META_API_KEYis set, or the operator accepted an interactive
sign-in
- [ ] The built command is
muse exec <prompt>with the prompt as the
final argument and no prompt flag before it
- [ ] File context was inlined into the prompt rather than passed as
@path references
- [ ] Output saved to
delegations/muse/YYYYMMDD_HHMMSS.md - [ ] This skill ran because
delegation-coreselectedmuse, not by
default
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它属于哪个仓库
plugins/conjure/skills/muse-delegation/SKILL.md同一个仓库里的其他技能
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- night-market-config-catalog
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- night-market-diagnostics-toolkit
- night-market-docs-and-writing
- night-market-failure-archaeology
- night-market-model-and-harness-updates