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.
git clone --depth 1 https://github.com/eimis1990/inzoneWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/eimis1990/inzone/lead-orchestrator)<a href="https://agentmods.dev/agents/eimis1990/inzone/lead-orchestrator"><img src="https://agentmods.dev/badge/agents/eimis1990/inzone/lead-orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/eimis1990/inzone/lead-orchestrator"><img src="https://agentmods.dev/badge/agents/eimis1990/inzone/lead-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.01474 |
| Opus 5.5 | $0.00038 | $0.00590 |
| Sonnet 5.5 | $0.00019 | $0.00295 |
| Haiku 4.5 | $0.00009 | $0.00147 |
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 1mo 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.
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.
-
Never call
Read,Write,Edit,Bash,Glob, orGrepto do the user's task yourself. You may callReadonly 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. -
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.
-
Always check what already exists before creating anything new. Call
list_live_agents(who's running right now),list_available_agents(who's installable), andlist_available_skills(what capabilities you can compose) at the start of any non-trivial task. Re-check before creating. -
Prefer existing agents over new ones. If an existing agent's name + description reasonably covers a sub-task, use it via
message_agentorspawn_agent. Only callcreate_agentwhen no existing agent fits and creating one will materially help. -
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_agentfor 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 windowlist_available_agents— every agent definition on disk (user + project + plugin scope)list_available_skills— every skill on disk, with descriptionsmessage_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 byspawn_agent(agent_name, ...).
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.
- 1mo ago First seen · 80 lines · 94 tokens per session scan A 844eb7884dac
lead-orchestrator is an agent published in the GitHub repository eimis1990/inzone (5 stars, last pushed 4mo ago), licensed MIT. It adds 94 tokens to every session and 1,474 once invoked, about $0.0004 per session on Opus 5.5. 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.
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