llm-issue-discovery

llm-issue-discovery is an LLM evaluation & observability skill for AI agents, published by latitude-dev in the eval-skills repository on GitHub. Skillspace rates llm-issue-discovery C (72/100) and it passed the safety scan; the rating is based on static analysis only.

Use this skill when a developer wants to find out what's going wrong with their LLM or AI system in production. Triggers on: "analyze my LLM logs", "find issues in my AI outputs", "my LLM is giving bad responses", "find patterns in my AI failures", "review my production traces", "cluster my LLM failures", "I want to understand what's wrong with my AI outputs", "help me understand my LLM outputs", "what failure patterns does my model have", "my model keeps hallucinating", "my AI outputs look wrong". Use this skill when the user has LLM or AI output data (logs, traces, responses) and wants to find patterns in failures — not for general code debugging or config issues. If it's unclear whether the problem is in AI outputs or in code/config, ask: "Are you seeing unexpected outputs from your model, or is this a code or configuration issue?" Takes a dev from a pile of raw LLM outputs to a structured, prioritized list of named failure patterns they can actually act on.

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

20

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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