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Design
Skill

/failure-recovery

What happens when an agent fails — retry, fallback, escalate, or graceful degradation.

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ai-design-skills
18844 skills18 commands
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$ npx -y skills add owl-listener/ai-design-skills --skill failure-recovery --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/failure-recovery

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The summary Claude sees to decide when to auto-load this skill.

What happens when an agent fails — retry, fallback, escalate, or graceful degradation.

SKILL.md

failure-recovery.SKILL.md
name: failure-recovery
description: What happens when an agent fails — retry, fallback, escalate, or graceful degradation.

Failure Recovery

Agents fail. Networks time out, models hallucinate, tools error, and edge cases surprise. Failure recovery design determines whether a failure becomes a dead end or a graceful detour.

Failure Types in Multi-Agent Systems

  • **Agent failure**: A single agent crashes, times out, or produces invalid output
  • **Handoff failure**: Context is lost or corrupted during transfer between agents
  • **Coordination failure**: Agents conflict, deadlock, or produce inconsistent results
  • **Resource failure**: External tools, APIs, or data sources are unavailable
  • **Cascading failure**: One agent's failure causes downstream agents to fail

Recovery Strategies

  • **Retry**: Try the same operation again. Works for transient errors (network timeouts, rate limits). Set a retry limit to avoid infinite loops.
  • **Fallback**: Switch to an alternative approach. A different agent, a simpler method, or a cached result.
  • **Escalation**: Pass the problem to a more capable agent or to a human. Used when the failure is beyond the current agent's ability to resolve.
  • **Graceful degradation**: Deliver a partial result rather than nothing. Tell the user what worked and what didn't.
  • **Compensation**: Undo the effects of a partially completed workflow before retrying or escalating.

Designing Recovery Paths

For each point in the workflow where failure is possible:

  • **What could fail?** List the failure modes
  • **What's the first recovery strategy?** Usually retry for transient errors
  • **What's the fallback?** If retry fails, what's the alternative?
  • **When do you escalate?** After how many retries or what type of failure?
  • **What does the user see?** Transparent about the failure or silently recovered?
  • **What's the worst case?** If all recovery fails, what's the graceful degradation?

User Experience of Failures

  • **Invisible recovery**: The system retries or falls back without the user noticing. Best for minor, quickly resolved failures.
  • **Transparent recovery**: The system tells the user something went wrong and how it's handling it. "This is taking longer than usual — trying an alternative approach."
  • **Participatory recovery**: The system asks the user to help. "I couldn't access your calendar. Can you check the connection?"
  • **Honest failure**: The system tells the user it can't complete the task and explains why. Offers alternatives.

Design Artefacts

  • Failure mode inventory per agent and per handoff
  • Recovery strategy specifications (retry limits, fallback paths, escalation triggers)
  • Cascading failure analysis
  • User experience specifications for each failure scenario
  • Recovery testing protocols
Read more
Ships withai-design-skills

Part of the Designer Skills suite. Install this collection and four more with one command in Claude Code: /plugin marketplace add Owl-Listener/designer-skills This repo still works on its own. The suite just gives everyone one front door.

Get the whole plugin

Other skills on ai-design-skills.