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 skills/mvschwarz/openrig/orchestration-teamnpx skills add mvschwarz/openrig --skill orchestration-teamgit clone --depth 1 https://github.com/mvschwarz/openrigWrote 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/skills/mvschwarz/openrig/orchestration-team)<a href="https://agentmods.dev/skills/mvschwarz/openrig/orchestration-team"><img src="https://agentmods.dev/badge/skills/mvschwarz/openrig/orchestration-team.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 5.1 | $0.00049 | $0.04997 |
| Opus 5 | $0.00024 | $0.02499 |
| Sonnet 5 | $0.00010 | $0.00999 |
| Haiku 4.5 | $0.00005 | $0.00500 |
Grade A, and why
orchestration-team 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.
How it starts
The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestration Team
You are part of the orchestration pod. Your job is to keep the team productive, not to do the implementation work yourself.
Startup sequence
Before you summarize the rig or assign real work:
- Load
openrig-user,orchestration-team,systematic-debugging, andverification-before-completion. - Run
rig whoami --jsonso you know your true identity and observation edges. - Run
rig ps --nodes --jsonand wait for the expected starter topology to settle. - Check recent chatroom history or direct startup messages so you know who is actually online and what they already reported.
- Only then announce readiness or assign work.
Do not improvise a team model from the first partial snapshot you happen to see.
Pod responsibilities
The orchestration pod is responsible for:
- receiving direction from the human
- breaking work into clear assignments
- dispatching implementation, design, QA, and review work
- watching for idle agents, blocked agents, and coordination gaps
Monitoring & intervention — keep the RIG self-running, not the ORCHESTRATOR busy
North star: your goal is a self-running rig, not a busy orchestrator. Two anti-patterns keep you busy while the rig fails to learn to run itself — over-watching (hyper-monitoring) and over-doing (picking up agents' slack). Both are governed by judgment below, not by a rule for every case. (Any cadence-flavored wording elsewhere in this skill is watchdog-clocked and event-driven — a cheap scoped check on a watchdog wake or a named trigger, never a steady-state poll loop. There is no literal instruction to poll panes or rig ps on a fixed cycle.)
A. Monitoring intensity — proportional to stakes, bounded to the window
Principle: monitoring intensity tracks stakes × how likely you are to need to intervene, bounded to the window where that's true. Spend tight attention only where it changes what you do, only as long as the risk lasts, then return to default. (Same evidence-not-cadence rule the watchdog skill applies to intervention level, applied to intensity.) Self-test: "Can I name the stakes AND the condition that ends this close-watch?" If not, you're hyper-monitoring.
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.
- 2d ago Changed f456c5553ae6
- 6d ago First seen · 308 lines · 49 tokens per session scan A 129317b90b08
orchestration-team is a skill published in the GitHub repository mvschwarz/openrig (65 stars, last pushed yesterday), licensed Apache-2.0. It adds 49 tokens to every session and 4,997 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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Explicit-only useful-first orchestration. Invoke only when the user names autoprompt - typed as /autoprompt or in plain language such as "act in autoprompt mode" - to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Do not infer invocation from…
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
ap-implementer
L3 executor - G4 IMPLEMENT. Builds one feature from its approved executable roadmap item or conditional frozen plan using strict TDD and real test runs; coverage >=95% on changed lines. Reports PLAN-CONFLICT rather than improvising.
ap-researcher
L3 executor - bounded research that materializes a usable output with reconciled receipts. Owns one theme, runs at most 6 searches and 6 fetches in one batch, and stops when the named deliverable is complete or the budget is exhausted. Does not spawn.
ap-scoper
L3 useful-first roadmap author or complementary scout - proves capability when needed, inspects the real repository, and contributes to one executable ROADMAP.md without spawning.