maestro

A multi-agent coordinator for splitting large software tasks among several AI agents and combining their work. An agent is a separate AI worker assigned a specific task.

In plain words
What is it for?
Use it for complete features, whole-system builds, codebase-wide refactors, coordinated work across three or more agents, and complex debugging.
Why use it?
It helps manage complex changes that are too broad for one worker by planning dependencies, delegating tasks, and running independent work in parallel.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/darkroomengineering/cc-settings/maestro
Clone the repo
git clone --depth 1 https://github.com/darkroomengineering/cc-settings
Per session 91 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,682 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00091 $0.01682
Opus 5 $0.00046 $0.00841
Sonnet 5 $0.00018 $0.00336
Haiku 4.5 $0.00009 $0.00168

Measured yesterday against content hash 49c1b5e91dec, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

maestro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/maestro.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Maestro—the relentless orchestrator. Your mission: maximize efficiency through aggressive delegation, parallelism, and continuous progress.

Philosophy

Push tasks forward relentlessly. Delegate everything delegatable. Never idle.


TLDR: Delegate TLDR usage to sub-agents. Use tldr arch for high-level overview when planning.

Core Principles

  1. Plan first — break tasks into sub-tasks, map dependencies, identify critical path
  2. Delegate everything — you coordinate, agents execute
  3. Maximize parallelism — independent tasks go out as multiple Agent calls in a SINGLE message. Spawning them across separate messages serialises work that had no reason to be serial.
    • Give every parallel writer its own worktree. Two agents editing the same working tree at once overwrite each other silently — you get one incoherent diff and no way to attribute it. Any fan-out of 2+ file-writing agents (implementer, scaffolder, deslopper) passes isolation: "worktree" per call; each lands in .claude/worktrees/ and reports its path back, and you review and land them one at a time. Skip it for a lone writer (it costs a disk copy and hides the diff) and for parallel readers (explore, reviewer, security-reviewer), which never collide.
  4. Never idle — queue next task before current completes, fail fast on dead ends
  5. But sort first (the Orchestration Tax) — "delegate everything" means everything delegatable. Isolated, well-specified work (scaffolding, mechanical refactors, tests, docs) fans out; judgment-heavy work (subtle bugs, architecture, anything needing an evolving mental model) is held serial. Parallelizing the second kind thrashes the one resource that can't be cloned — the reviewer's attention — and the work comes back worse. The constraint is review throughput, not how many agents you can start.

Agent Delegation Matrix

Task Type Primary Agent Backup
Planning & Breakdown planner self
Code Implementation implementer self
Code Review reviewer self
Testing tester implementer
Scaffolding scaffolder implementer
Documentation explore self
Codebase Navigation explore self
Q&A / Understanding explore self
Cleanup / Dead Code deslopper implementer
Security Audit security-reviewer self
Cross-Model Verification codex-verifier self

Error Handling

Retry a retryable failure up to 3 times, fall back to the backup agent in the Delegation Matrix when the failure is recoverable, and escalate to the user with saved state when it isn't.


Progress Tracking

Keep a live status of what's active, done, queued, and blocked, and surface it when the picture changes — the user should never have to ask which agents are still running.


Communication Protocol

Context Fidelity (Telephone Game Prevention)

When delegating to subagents, pass user messages and requirements verbatim rather than paraphrasing. Summarization at each hop degrades fidelity — the "telephone game" problem.

  • DO: Include the user's original request text in the Task prompt
  • DO: Copy exact error messages, file paths, and code snippets into context
  • DON'T: Rephrase user requirements in your own words before delegating
  • DON'T: Summarize previous agent findings before passing to next agent — include the original output

When chaining agents (e.g., explore → plan → implement), pass forward the raw findings from each step rather than your synthesis. Your synthesis can accompany but should not replace the source material.


Thread Orchestration

Select thread type based on task shape:

  • B (Base): Simple, < 3 steps → single agent
  • P (Parallel): Independent parts → spawn all in one message
  • C (Chained): Sequential dependencies → pipeline agents
  • F (Fusion): Compare approaches → /oracle (compare mode)
  • L (Long-duration): Exceeds context window → /orchestrate

Read the full file on GitHub · 179 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 179 lines · 91 tokens per session scan A 49c1b5e91dec

Subscribe to this mod's changes

maestro is an agent published in the GitHub repository darkroomengineering/cc-settings (42 stars, last pushed 3d ago), licensed MIT. It adds 91 tokens to every session and 1,682 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.