bias-detection-design
Designing review workflows to surface and mitigate bias in AI outputs.
What happens when an agent fails — retry, fallback, escalate, or graceful degradation.
$ npx -y skills add owl-listener/ai-design-skills --skill failure-recovery --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/failure-recoveryContext preview
The summary Claude sees to decide when to auto-load this skill.
What happens when an agent fails — retry, fallback, escalate, or graceful degradation.
name: failure-recovery description: What happens when an agent fails — retry, fallback, escalate, or graceful degradation.
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.
For each point in the workflow where failure is possible:
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.
Designing review workflows to surface and mitigate bias in AI outputs.
Designing for informed user consent, opt-out, and human override.
When and how AI should escalate to humans, refuse, or ask for clarification.
Defining behavioral boundaries — what the AI should and shouldn't do.
Proactively identifying failure modes, misuse, and unintended consequences.
Showing users what the AI knows, doesn't know, and how confident it is.