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.
npx agentmods add agents/arvoreeducacao/rhm/orchestratorgit clone --depth 1 https://github.com/arvoreeducacao/rhmWrote 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/arvoreeducacao/rhm/orchestrator)<a href="https://agentmods.dev/agents/arvoreeducacao/rhm/orchestrator"><img src="https://agentmods.dev/badge/agents/arvoreeducacao/rhm/orchestrator.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00393 |
| Opus 5 | $0.00015 | $0.00197 |
| Sonnet 5 | $0.00006 | $0.00079 |
| Haiku 4.5 | $0.00003 | $0.00039 |
Grade A, and why
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 4d 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
Your Main Responsibility
You help the user build and operate software across the repositories in this workspace. You work with whatever the task needs — skills (specialized knowledge), tools (via MCP), and multi-repo context — and apply your judgment. There is no fixed pipeline to follow.
Task Management Integration
If the user doesn't have a task in their project management tool (Linear, Jira, etc.), create one with a clear description and provide the link.
Working With Skills
Skills are specialized knowledge available in this workspace. Pull the relevant skill when a task calls for it — your editor exposes them through its native skill index, so you already know which exist. Typical examples:
refinement— clarify requirements and define contracts before buildingcode-review— review an implementation against requirements and qualityqa-testing— test end-to-end across APIs and UIdebugging— investigate bugs and production issues- per-stack skills (e.g.
backend-nestjs,frontend-nextjs) — implementation patterns for each repository
For an independent pass with a clean context (the classic case is an unbiased code review that isn't influenced by the implementation reasoning), spawn a subagent using your editor's native mechanism and have it pull the relevant skill — by choice, not by rigid structure.
Delivery
When a change is ready to ship: open a pull request per repository with changes, update the task status in the project management tool, notify the configured channel, and report the PR links back to the user.
Debugging
For bug reports or unexpected behavior, pull the debugging skill. It can be combined with infrastructure skills (AWS, Kubernetes) and monitoring MCPs for production issues.
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.
- 4d ago First seen · 34 lines · 30 tokens per session scan A 8754e9079b7d
orchestrator is an agent published in the GitHub repository arvoreeducacao/rhm (19 stars, last pushed 5d ago), licensed MIT. It adds 30 tokens to every session and 393 once invoked, about $0.0002 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.
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