oversight-team — Claude Code skill for monitoring agent rigs
This skill guides a monitor that checks other agent rigs for drift and chooses a measured response. It waits for a signal instead of polling continuously.
npx skills add mvschwarz/openrig --skill oversight-team -a claude-codeWhat oversight-team does
oversight-team lays out how to monitor other rigs without taking over their work. Its detectors look for unfinished queue items with no handoff, activity that produces no shipped change, off-task work, and unusual token consumption. Check transcripts, Git history, or queue state before acting; apparent idleness alone is not enough.
The response starts with a ping to the rig’s orchestrator, followed by a Refocus reminder through watchdog if needed. Problems an agent-level nudge cannot resolve go to a human. Cheap models read logs and transcripts, while a more expensive watcher makes decisions from summaries. This is an instruction skill, not a script bundle. Its token-burn detector checks consumption at a point in time, not per-agent usage over time.
What it helps with
- Catch a task that stopped without handing off its work
- Spot a process that produces commits but no shipped change
- Check whether a rig has wandered off task
- Find excessive monitoring tied to token consumption
- Choose whether to ping an orchestrator or escalate to a human
Example prompts for the agent
- Check whether a task stopped without a handoff, and verify it in the transcript.
- Use the logs and Git history to see whether this rig is still on task.
- This rig is consuming a lot of tokens; check for a vigilant monitoring loop.
How to install oversight-team
1Skills CLI (Vercel)
npx skills add mvschwarz/openrig --skill oversight-team -a claude-code2Manually: put the files in place
~/.claude/skills/oversight-team/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/oversight-team/
1Skills CLI (Vercel)
npx skills add mvschwarz/openrig --skill oversight-team -a codex2Manually: put the files in place
.agents/skills/oversight-team/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add mvschwarz/openrig --skill oversight-team -a cursor2Manually: put the files in place
.cursor/skills/oversight-team/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install mvschwarz/openrig oversight-team2Manually: put the files in place
.github/skills/oversight-team/SKILL.md1Skills CLI (Vercel)
npx skills add mvschwarz/openrig --skill oversight-team -a gemini-cli2Platform CLI
gemini skills install https://github.com/mvschwarz/openrig --path skills/_canonical/pods/oversight-teamManually: put the files in place
.devin/skills/oversight-team/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add mvschwarz/openrig --skill oversight-team -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about oversight-team
How do I install oversight-team in Claude Code?
Run npx skills add mvschwarz/openrig --skill oversight-team -a claude-code. The skill is installed at ~/.claude/skills/oversight-team/SKILL.md.
What does oversight-team do?
It explains how to monitor other agent rigs, verify signs of drift, and choose a low-disruption intervention. It is not for orchestrating your own rig.
How does oversight-team detect token burn?
The described detector checks consumption at a point in time and flags unusually high consumers for inspection. It does not track per-agent token use over time.
Source text
SKILL.md · Apache-2.0
---
name: oversight-team
description: Use when you are a seat on the oversight pod (a standing monitor-mode rig that keeps OTHER rigs healthy), configuring or running the drift detectors, or choosing whether to intervene vs escalate. Covers the pull-not-poll posture, the v0 detectors (premature-park, process-drift, off-task, token-burn), the intervention ladder (orchestrator-ping -> refocus -> human escalation), and the cheap+deep model economics. NOT for orchestrating your OWN rig (orchestration-team) and NOT the intervention primitive mechanics (watchdog).
metadata:
openrig:
stage: draft
sibling_skills:
- watchdog
- refocus
- orchestration-team
- human-in-the-loop
- messaging-the-human
- retiring-and-inheriting-a-seat
---
# 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 watchdog` policies, message shape) — that's `watchdog`.
- A single stuck seat needs recovery — the owning orchestrator or `watchdog` handles 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.
## Interventions — least-disruptive first
1. **Orchestrator-ping** — nudge the pod's own orchestrator to realign. They run their rig; you
prompt, you do not seize.
2. **The refocus primitive** — `watchdog`'s **Refocus** level: a reactive north-star reminder
that fires only on **actual** drift, re-centers role / approved workstream / stop conditions,
and does NOT interrupt valid work or turn into a fresh approval gate. Use `watchdog` for the
message shape and the cadence discipline.
3. **Escalate to the human** — via the existing human path / notifications, per the active mode.
Reserve for what an agent-level nudge cannot fix.
## Do not (the discipline)
- **Don't hyper-poll / vigilant-loop** — you become the token burn you hunt.
- **Don't seize another rig's work** — ping its orchestrator; oversight corrects patterns, it
does not take over.
- **Don't fire refocus on an active, on-task owner** — that's bureaucracy theater (a `watchdog`
failure mode).
- **Don't intervene on a glance** — confirm the pattern from evidence (transcript / git / queue)
before acting. A false alarm costs the fleet trust and tokens.
- **Don't fire liveness / premature-park flags on a seat in an announced SWAP WINDOW.** A seat mid-handover
looks idle/parked to the detectors. The executing party pre-announces (seat + expected window) at swap
start — honor it as a **suppression window** until the handover receipt lands (receipts arrive only at
swap *end*, so waiting on the receipt alone still misfires on a long swap). See `retiring-and-inheriting-a-seat`.
## Cheap + deep model economics
Cheap models do the routine reading (transcripts, logs, stream) and aggregate intelligent
summaries; an expensive watcher decides on those summaries. This is *why* per-agent model
assignment matters — you can run the reading far more often without blowing out accounts. Design
the pod so the deep model never touches the raw firehose.
## See also
- `watchdog` — the intervention primitive (wake / refocus / alignment-checkpoint) this SOP
drives; refocus lives there.
- `refocus` — the drift doctrine `watchdog` operationalizes.
- `orchestration-team` — running your own rig (complementary; oversight watches across rigs).
- `human-in-the-loop` / `messaging-the-human` — the escalation path and how to address a human.
- `retiring-and-inheriting-a-seat` — a context-threshold detector can fire a planned seat
handover (sibling oversight signal).
© mvschwarz · Apache-2.0 · mvschwarz/openrig