Error Recovery workflow

SkillAI & models

Handle failures and errors during workflow. Use when build breaks, tests fail unexpectedly, or agent gets stuck. Semi-automatic recovery with user confirmation for destructive actions.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Error Recovery workflow skill

What this skill tells your AI

The instructions your AI receives, as published by diegosouzapw/awesome-omni-skill in skills/data-ai/agent-ops-recovery/SKILL.md and read by ahel’s review.

Trigger conditions

Use this skill when:

  • Build/lint fails unexpectedly after agent changes
  • Tests fail that were passing in baseline
  • Agent encounters ambiguity it cannot resolve
  • Implementation is stuck or going in circles

Recovery procedure

Step 1: Diagnose (invoke debugging)

For non-trivial failures, invoke agent-ops-debugging:

  1. Apply systematic debugging process:
    • Reproduce the issue consistently
    • Define expected vs actual behavior
    • Form hypothesis about root cause
  2. Use debugging output to inform recovery decision
  3. If root cause unclear after initial analysis, continue debugging before recovery

Step 2: Assess rollback options

  • Option A: Fix forward — issue is minor, can be resolved quickly
  • Option B: Partial rollback — revert specific file(s) to last good state
  • Option C: Full rollback — revert all agent changes since checkpoint
  • Option D: Escalate — document the issue, mark task blocked, ask user

Step 3: Propose action

Present options to user with:

  • What will be reverted/changed
  • Risk assessment
  • Recommendation

Step 4: Execute (with confirmation)

  • For non-destructive actions (fix forward): proceed
  • For destructive actions (rollback): ask user first
  • Update .agent/focus.md with recovery action taken

Destructive actions (require confirmation)

  • git reset
  • git checkout -- <file> (discard changes)
  • git revert
  • Deleting files
  • Overwriting files with previous versions

Non-destructive actions (can proceed)

  • git stash
  • Reading files
  • Running diagnostics
  • Updating focus/tasks with findings

Post-recovery

  1. Update .agent/focus.md with what happened
  2. Invoke agent-ops-tasks to create issue for root cause investigation
  3. Update .agent/memory.md with "pitfall to avoid" if applicable
  4. Re-run baseline comparison before continuing

Issue Discovery After Recovery

After recovery, invoke agent-ops-tasks discovery procedure:

  1. Create issue for the incident:

    📋 Recovery completed. Create issue to track root cause?
    
    Suggested:
    - [BUG] Investigate: {description of what failed}
      - What happened: {failure description}
      - Recovery action: {what was done}
      - Root cause: TBD
    
    Create this issue? [Y]es / [N]o
    
  2. If pattern detected, create prevention issue:

    This failure pattern has occurred before. Create improvement issue?
    
    - [CHORE] Add validation to prevent {failure type}
    - [TEST] Add regression test for {scenario}
    
    Create these? [A]ll / [S]elect / [N]one
    
  3. After creating issues:

    Created {N} issues for tracking. What's next?
    
    1. Investigate root cause now (BUG-0024@abc123)
    2. Continue with original work (defer investigation)
    3. Review recovery actions
    

Signals

GitHub stars
57
Forks
19
Last commit
Mar 2026
Advanced
Catalog kind
skill
Gateway key
agent-ops-recovery
Source
github.com/diegosouzapw/awesome-omni-skill