Agent Orchestrator is a local desktop workspace for running and supervising multiple coding agents, giving each task its own session, workspace, branch, and feedback loop. It is for developers coordinating agent fleets across repositories, pull requests, CI runs, reviews, and merges. The catalogue entries are commands, skills, and instructions for working with this orchestrator.
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/Untrivial-ai/agent-orchestratorWrote 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/commands/untrivial-ai/agent-orchestrator/doctor)<a href="https://agentmods.dev/commands/untrivial-ai/agent-orchestrator/doctor"><img src="https://agentmods.dev/badge/commands/untrivial-ai/agent-orchestrator/doctor/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/commands/untrivial-ai/agent-orchestrator/doctor"><img src="https://agentmods.dev/badge/commands/untrivial-ai/agent-orchestrator/doctor.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 | $0.00000 | $0.00103 |
| Opus 5 | $0.00000 | $0.00051 |
| Sonnet 5 | $0.00000 | $0.00021 |
| Haiku 4.5 | $0.00000 | $0.00010 |
Grade A, and why
doctor 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 10d 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.
What it actually says
ao doctor
Run local AO health checks. Use this to diagnose setup problems or verify the environment is correctly configured.
Syntax
ao doctor [flags]
Flags
| Flag | Meaning | Default / Required |
|---|---|---|
--json |
Output health checks as JSON | - |
Examples
# Run health checks
ao doctor
# Get health check results as JSON
ao doctor --json
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.
- 10d ago First seen · 28 lines · 0 tokens per session scan A 1ac311bab7de
doctor is a command published in the GitHub repository Untrivial-ai/agent-orchestrator (11,134 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 103 tokens. 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.
Other commands, from other repositories
re-process
Traite les corrections identifiees dans le rapport de validation d'une analyse. Modifie le code pour resoudre les points du rapport sans faire d'analyse supplementaire.
debug-pod
Debug a failing or unhealthy Kubernetes pod by analyzing events, logs, and configuration.
map
Generate a dependency map showing how modules and files relate to each other in the codebase.
root-cause
Use when any test fails, bug appears, or behaviour surprises you, before proposing a fix - find the cause and prove it, by reading real evidence, tracing bad values back to their origin, comparing against a working case, and testing one hypothesis at a time.
sync-to-copilot
Sync skills and instructions from Claude or Codex to GitHub Copilot CLI.
analyze
Deep analysis with Hiroshi(Oracle).