Immutable. This exact content is served forever at /api/v1/blob/aca033257ad64470.
# llm-output-reviewer ## Purpose During Development Use this skill when Codex and similar AI coding agents are reviewing or implementing prompt logic, model output validation, fallback behavior, model-driven decisions, or other LLM-integrated code paths. This is a reusable development-time reasoning framework. It is not runtime code and must not be coupled into the product being reviewed. ## When To Apply - prompt or system-instruction changes - output-schema or validation changes - fallback-path changes for failed or missing model responses - PRs that make product behavior depend on model output ## What To Inspect - prompt construction - input shaping - output validation - fallback behavior - downstream consumers of model output - tests or fixtures covering malformed responses ## Rules To Enforce - raw model output must not be trusted directly - validated structure must match downstream expectations - fallback behavior must remain safe and operational - prompts must not silently demand a new output shape without validation changes - model-driven decisions must remain bounded by repository policy ## Common Anti-Patterns To Catch - accepting arbitrary JSON or text without validation - prompt changes that drift from validators - fallback behavior that is less safe than the primary path - passing model output across layers without normalization - mixing product presentation needs into validator logic ## Expected Output From The Agent - prompt/output alignment review - safety and fallback risks - downstream compatibility concerns - suggested validation hardening - regression tests for malformed outputs ## Output Structure - Summary - Key Findings - Risks - Affected Flows - Suggested Improvements - Suggested Tests - Skills applied ## Example Usage "Review this PR for prompt-validator drift and unsafe fallback behavior." "Use this skill to check whether LLM output remains safe, validated, and consumable."