Skills

Diagnose Stopped Work

Diagnoses why agent work failed, stalled or looped, and points to the fix workflow.

Install

npx skills add paperclipai/paperclip --skill diagnose-why-work-stopped -g -a claude-code -y
Repository
paperclipai/paperclip110k
Category
AI and agents
Updated
3d ago
License
MIT
Context cost
Lightabout 395 tokens
Runs scripts
No, instructions only

What it does

Compatibility entry point for failed, stalled, looping, or over-recovered Paperclip work. Use fix-failed-paperclip-run for the full diagnosis, regression, repair, real verification, and green-PR workflow; honor an explicitly requested diagnosis-only scope.

Diagnose Why Work Stopped

Use Fix Failed Paperclip Run. It owns the current workflow: find the first causal failure, reproduce it red, repair the shared contract, test second-order effects, verify the real workflow, and deliver a PR with passing checks. A normal request to fix stopped work continues through that workflow without a separate plan-approval gate.

If the user or calling workflow explicitly asks for diagnosis only or requires approval before implementation, perform the investigation and safety analysis within that scope. For example, a Terminal-Bench diagnosis child does not override the loop's board approval boundary. Keep the next action and its owner explicit.

For issue-tree diagnosis, read the current doc/execution-semantics.md, inspect the relevant subtree and recent repairs, and classify non-progressing nodes:

  • Genuine wait: a named human or external dependency must act.
  • Agent-actionable but unrouted: authorized useful work lacks a live path.
  • Already covered: existing work owns the next action; do not duplicate it.

Preserve these three invariants together:

  1. Productive work has a real next action and owner.
  2. Only genuine blockers stop work, including approval, credentials, and budget.
  3. Recovery is bounded and cannot recursively recover itself.

Frame any repair as a general behavioral contract, check it against a productive counterexample, and follow the new skill through the authorized finish line. Historical task links and private incident access are not required.

More in AI and agents