Human In The Loop
Route decisions to humans with durable queues and attention tracking.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up β so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/human-in-the-loop-mvschwarz/β the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates β they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description β no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the βWhat this skill doesβ section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
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 β 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.
What this skill does
Human In The Loop
The primitive that treats humans as durable network participants β attention surfaces, queues, decision records, routing semantics β 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.mdalready 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 | Mark closed; create next-owner qitem from plan |
| human gate | Genuine decision needed (usage limits, provider auth, product-intent ambiguity, roadmap tradeoff) | 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.mdalready 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 β human decision recorded through UI β 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 β 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 β 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 β 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-handoffskill β durable handoff via queue items; human-in-the-loop is the human-side complementwatchdogskill β when to wake (humans included) vs no-oplooping-workflows(convention) β the looping-workflows convention covers loop closeouts; human-in-the-loop is the escape hatch
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