Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Owl-Listener/ai-design-skills --skill failure-recoverygit clone --depth 1 https://github.com/Owl-Listener/ai-design-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/owl-listener/ai-design-skills/failure-recovery)<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/failure-recovery"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/failure-recovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/failure-recovery"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/failure-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.00580 |
| Opus 5 | $0.00010 | $0.00290 |
| Sonnet 5 | $0.00004 | $0.00116 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
failure-recovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 38 lines · 21 tokens per session scan A 512e3384166e
failure-recovery is a skill published in the GitHub repository Owl-Listener/ai-design-skills (173 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 580 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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