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muse-delegation

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 context.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: muse-delegation description: 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. alwaysApply: false category: delegation-implementation tags:

  • muse
  • meta
  • cli
  • delegation
  • large-context dependencies:
  • delegation-core tools:
  • muse
  • delegation_executor.py usage_patterns:
  • muse-cli-integration
  • repository-scale-analysis
  • headless-ci-execution complexity: intermediate model_hint: standard estimated_tokens: 600 references:
  • delegation-core/shared-shell-execution.md

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-core selected muse for the task
  • Repository-scale reading where Muse Spark 1.2's 1M-token context helps
  • Work that should run unattended, since muse exec is designed for CI

When NOT To Use

  • META_API_KEY is unset and the run cannot be interactive
  • A specific model must be selected. Meta documents no --model flag 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

PropertyValue
Binarymuse
Headless formmuse exec <prompt>
Prompt deliverypositional, no flag
Version probemuse --version
Auth probenone published
AuthMETA_API_KEY
File contextinlined, 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

  • muse resolves on PATH and muse --version answers
  • META_API_KEY is 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-core selected muse, not by default
Gespeicherte Skills