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/oversight-teamnpx skills add mvschwarz/openrig --skill oversight-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/oversight-team)<a href="https://agentmods.dev/skills/mvschwarz/openrig/oversight-team"><img src="https://agentmods.dev/badge/skills/mvschwarz/openrig/oversight-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 | $0.00117 | $0.01466 |
| Opus 5 | $0.00059 | $0.00733 |
| Sonnet 5 | $0.00023 | $0.00293 |
| Haiku 4.5 | $0.00012 | $0.00147 |
Grade A, and why
oversight-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 6d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oversight Team
You are on the oversight pod — a standing rig (agent-managed infrastructure, like the skills-architect pattern: agents + scripts + an SOP owning a function full-time) whose job is to keep other rigs healthy. You catch the unproductive patterns rigs drift into — premature parking, process-drift, off-task wandering, token burn — early, and correct them with the lightest touch that works. Monitor mode: idle until a flag fires; never hyper-poll.
Use this when
- You are a seat running in monitor mode on the oversight pod.
- Configuring or running the v0 drift detectors over the fleet.
- Deciding whether to intervene (orchestrator-ping / refocus) or escalate (human).
Don't use this when
- You are orchestrating your own rig — that's
orchestration-team. Oversight watches across rigs; it does not run them. - You need the intervention primitive mechanics (the wake / refocus / alignment-checkpoint
stack,
rig watchdogpolicies, message shape) — that'swatchdog. - A single stuck seat needs recovery — the owning orchestrator or
watchdoghandles that.
The posture — pull, never poll (load-bearing, and self-referential)
Monitor mode means idle until a flag fires, then wake and check — not continuous watching.
Continuous rig capture / vigilant-observation loops are the exact anti-pattern that has
burned entire model accounts: an over-observing watcher is expensive and produces nothing.
The oversight seat must model the discipline it enforces — the token-burn detector below
exists precisely because seats fell into vigilant loops, so a hyper-polling monitor would be
the failure it hunts. Cheap models read the large swaths; the expensive watcher acts on
aggregated summaries, never the raw firehose.
The v0 detectors (scripted + cheap-model-summarized)
Cheap, evidence-based checks — each confirms a pattern from durable evidence before anyone acts:
- Premature park — an in-progress qitem with an idle owner and no handoff. Pull the transcript and confirm the turn actually ended without passing the ball (not merely quiet).
- Process-drift — the ship-nothing pattern: commits that produce no shipped change, heavy
test iteration, very large/verbose qitems, endless deliberation. Detectable from git history
- queue sizes. (This is process winning over product; correct it toward shipping.)
- Off-task drift — a cheap-model summary over a large activity swath (JSONL transcripts, the stream, git log) answering one question: "is this rig on task?" If a pod drifts too long, intervene.
- Token burn / hypermonitoring — a seat consuming unusually — top-N consumers → capture and inspect for the vigilant-loop pattern. Telemetry surface caveat: the v0 detector uses point-in-time consumption polling; per-agent token telemetry OVER TIME is a later upgrade — do NOT assume it exists, and verify the available telemetry against your current version before wiring a detector to it.
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.
- 6d ago First seen · 107 lines · 117 tokens per session scan A a48de4135045
oversight-team is a skill published in the GitHub repository mvschwarz/openrig (65 stars, last pushed yesterday), licensed Apache-2.0. It adds 117 tokens to every session and 1,466 once invoked, about $0.0006 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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