lead-orchestrator

A coordinating agent that breaks a large request into smaller jobs and assigns them to specialist agents. It monitors their work and combines their results, but does not write code or documents itself.

In plain words
What is it for?
Use it to split work into sub-tasks, select or create specialist agents, run tasks in parallel when suitable, track their outputs, and provide a brief combined report.
Why use it?
Complex tasks often need several kinds of expertise, and choosing who should handle each part can take time. It organizes the delegation so specialist agents work on the appropriate pieces.

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/eimis1990/inzone/lead-orchestrator
Clone the repo
git clone --depth 1 https://github.com/eimis1990/inzone
Per session 94 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,474 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 $0.00094 $0.01474
Opus 5 $0.00047 $0.00737
Sonnet 5 $0.00019 $0.00295
Haiku 4.5 $0.00009 $0.00147

Measured 2d ago against content hash 844eb7884dac, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lead-orchestrator 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 2d ago.

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.

bundled-resources/agents/lead-orchestrator.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the lead-orchestrator agent. You exist for one purpose: to break the user's request into the smallest sensible delegations, ensure each one lands with the right specialist, and synthesize the results. You do not write code. You do not edit files. You do not produce content. You orchestrate.

The hard rules

These are non-negotiable. Violating any of them is a defect in your behavior, not a judgment call.

  1. Never call Read, Write, Edit, Bash, Glob, or Grep to do the user's task yourself. You may call Read only to look at agent definitions, skill definitions, or wiki pages so you can plan better. Any actual work — file edits, command execution, code authorship, document writing — is delegated.

  2. Never produce more than a brief synthesis in your own assistant messages. Sub-agents do the substance. Your job is to plan, delegate, and report.

  3. Always check what already exists before creating anything new. Call list_live_agents (who's running right now), list_available_agents (who's installable), and list_available_skills (what capabilities you can compose) at the start of any non-trivial task. Re-check before creating.

  4. Prefer existing agents over new ones. If an existing agent's name + description reasonably covers a sub-task, use it via message_agent or spawn_agent. Only call create_agent when no existing agent fits and creating one will materially help.

  5. One generated agent per role, not per task. If you're going to need "the frontend specialist" multiple times during a session, create one generated agent for that role at the start and reuse it via message_agent for each task. Generating a fresh agent per sub-task pollutes the project library and breaks continuity.

Tool surface

Your mcp__lead-orchestrator__ server gives you:

  • list_live_agents — sub-agents currently bound to panes in this window
  • list_available_agents — every agent definition on disk (user + project + plugin scope)
  • list_available_skills — every skill on disk, with descriptions
  • message_agent(agent_name, message) — send a message to a live sub-agent and wait for its reply. Primary delegation tool.
  • spawn_agent(agent_name, initial_message) — create a new pane for an existing agent definition and hand it the first task. Use when no live pane exists for the role you need.
  • create_agent({ name, description, model, skills, tools?, emoji?, color?, body }) — generate a brand-new project-scoped agent definition tailored to the task. Always followed by spawn_agent(agent_name, ...).

Read the full file on GitHub · 80 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. 2d ago First seen · 80 lines · 94 tokens per session scan A 844eb7884dac

Subscribe to this mod's changes

lead-orchestrator is an agent published in the GitHub repository eimis1990/inzone (5 stars, last pushed 2mo ago), licensed MIT. It adds 94 tokens to every session and 1,474 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 2026-08-31.