Use when classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participan
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add mvschwarz/openrig --skill human-in-the-loop -a cursor -y
Use when classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.
Questions
How do I install human-in-the-loop?
Download packages/daemon/specs/agents/shared/skills/core/human-in-the-loop/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does human-in-the-loop live?
The publisher keeps it at https://github.com/mvschwarz/openrig.
Which agents can use human-in-the-loop?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
Use when classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.
name: human-in-the-loop
description: Use when classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.
metadata:
openrig:
stage: factory-approved
sibling_skills:
- queue-handoff
- workflow-runtime
- watchdog
- refocus
- looping-workflows
- intake-routing
- attention-queue
- dispatching-parallel-agents
- subagent-driven-development
- control-plane-capabilities
- status-not-chat-orchestrator
- control-plane-queue
- control-plane-watchdog
- control-plane-workflows
- control-plane-delivery-loop
- control-plane-rollout-manager
Human In The Loop
The primitive that treats humans as durable network participants —
attention surfaces, queues, decision records, routing semantics — not
as ad-hoc chat receivers.
Autonomy is not the absence of humans; it is knowing when human
judgment is needed and making that handoff crisp.
Use this when
A slice closeout needs classifying: auto-continue, human gate, or park
A real decision needs to land in front of a human (usage limits, provider auth, roadmap tradeoff, product-intent ambiguity)
Designing a human queue/dashboard surface
Returning a hot potato to orchestration after human approval
Don't use this when
The slice closeout is clean and PROGRESS.md already names the next safe slice. Default RSI conveyor continues; do NOT manufacture a human gate.
The escalation is just a status update. Humans are participants for decisions, not narration.
The next owner is another agent. Use queue-handoff, not human-in-the-loop.
The 3-class closeout classification
In a productized daemon-backed version, closeout classifies the next
step BEFORE touching the human queue:
Class
When
Action
auto-continue
Slice closes cleanly, next named slice in workstream plan
Create human queue item with proof + decision text + recommended default + action outcomes
park
Intentionally stop the conveyor (e.g., waiting on external)
Stop with reason + resumption path
Failure modes (5)
Human decision needed, but the rig only mentions it in chat. Decisions belong as durable attention items, not chat messages.
Human queue item lacks enough plain-English context for a decision. Include proof + decision text + recommended default + action outcomes.
Human response updates a file but does not wake the next owner. Approval should return the hot potato; feedback should create the next durable qitem.
The dashboard shows too much raw rig state and hides the actual decision queue. Decision queue is the primary surface; rig state is secondary.
A clean closeout is parked on the human even though PROGRESS.md already names the next safe slice. Don't manufacture human gates.
Proof standard (both paths)
A trustworthy human-in-the-loop system proves both directions:
Blocking gate path: real item routed to human → human decision recorded through UI → resulting hot-potato handoff wakes correct next owner
Non-blocking closeout path: proof inspectable by human, but orchestrator continues to next named slice without manufacturing a human gate
A primitive that only wakes humans is not trustworthy. It must also know when NOT to.
Product shape (SHIPPED — Mission Control, PL-005)
This surface has shipped as Mission Control (product UI, /mission-control
route; actions via POST /api/mission-control/action). The seven verbs the
human acts with:
approve (returns the hot potato to orchestration or the chosen owner)
deny (reject the item)
route (send to a different owner)
annotate (add context without action)
hold (intentional pause with reason)
drop (mark not-actionable)
handoff (hand to a specific next owner — creates the next durable qitem)
Approval returns the hot potato to orchestration or the chosen owner;
feedback creates the next durable qitem rather than only mutating the source
queue file — enforced by the shipped verbs (handoff/route create qitems).
See docs/as-built/architecture/mission-control.md.
Long-term shape
Likely needs multiple humans with different scopes, not a singleton
human attention feed. Different humans own different decision
domains; queue items route by scope.
See also
queue-handoff skill — durable handoff via queue items; human-in-the-loop is the human-side complement
watchdog skill — when to wake (humans included) vs no-op
looping-workflows (convention) — the looping-workflows convention covers loop closeouts; human-in-the-loop is the escape hatch
How do I install human-in-the-loop?
Download packages/daemon/specs/agents/shared/skills/core/human-in-the-loop/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does human-in-the-loop live?
The publisher keeps it at https://github.com/mvschwarz/openrig.
Which agents can use human-in-the-loop?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.