failure-taxonomy
Classifying AI failures — hallucination, refusal, irrelevance, tone mismatch, latency.
- Installs
- 132
- Last 24h
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- Trending rank
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- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/ai-design-skills --skill failure-taxonomy- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads failure-taxonomy automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Failure Taxonomy
Not all AI failures are the same. A hallucination is different from a refusal, which is different from a tone mismatch. A failure taxonomy classifies failure types so teams can track, prioritise, and address them systematically.
Failure Categories
Content Failures:
- Hallucination: The AI presents false information as fact
- Inaccuracy: The AI gets details wrong (dates, numbers, names)
- Incompleteness: The AI misses important information
- Irrelevance: The AI's response doesn't address the user's actual question
- Contradiction: The AI contradicts itself within or across responses Behavioral Failures:
- Inappropriate refusal: The AI refuses a reasonable request
- Missing refusal: The AI fulfils a request it should have declined
- Tone mismatch: The AI's tone is wrong for the context
- Persona break: The AI drops out of its defined persona
- Over-generation: The AI produces far more than needed Technical Failures:
- Latency: Response takes too long
- Truncation: Response is cut off
- Format errors: Output is in the wrong format or structure
- Tool failures: The AI attempts to use a tool and fails
- Context loss: The AI loses track of conversation history Safety Failures:
- Harmful content: The AI generates content that could cause harm
- Privacy violation: The AI reveals sensitive information
- Bias manifestation: The AI's output shows bias against a group
- Manipulation: The AI's output could be used to deceive or manipulate
Severity Levels
- Critical: Causes harm or creates serious trust violation. Requires immediate fix.
- High: Significantly degrades user experience or task success. Fix within days.
- Medium: Noticeable quality issue that users can work around. Fix within weeks.
- Low: Minor quality issue. Track and batch with other fixes.
Using the Taxonomy
- Logging: Classify every detected failure by type and severity
- Trending: Track failure type frequency over time
- Prioritisation: Address highest-severity, highest-frequency failures first
- Root cause analysis: Group failures by type to identify systemic causes
- Prevention: Use failure patterns to inform guardrail design and prompt improvements
Design Artefacts
- Failure taxonomy reference document
- Failure logging templates
- Severity classification rubric
- Failure trend dashboards
- Root cause analysis protocols
FAQ
What does the failure-taxonomy skill do?
Classifying AI failures — hallucination, refusal, irrelevance, tone mismatch, latency.
How do I install failure-taxonomy?
Run npx skills add https://github.com/owl-listener/ai-design-skills --skill failure-taxonomy in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/failure-taxonomy/ (personal) or .claude/skills/failure-taxonomy/ (project).
Which AI agents can use failure-taxonomy?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is failure-taxonomy safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains failure-taxonomy?
It is published by owl-listener in owl-listener/ai-design-skills. It has 132 recorded installs.
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