review-prompt

Solid

Review LLM prompts against the prompt-engineering skill's principles — leading with where each line came from — and report the findings without modifying files. Use when reviewing prompt quality, auditing a prompt, evaluating a system prompt, or checking whether prompt issues are high-confidence and fixable.

AI & Automation 73 stars 10 forks Updated 3 days ago MIT

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Quality Score: 87/100

Stars 20%
62
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

Review LLM prompts. Report findings without modifying files — this skill diagnoses; it never edits the prompt. **First**: invoke the prompt-engineering skill to load the principles. Evaluate the prompt against them. The provenance question leads: for each line, where did it come from — a user ruling, knowledge outside what the run will read, or a default it counteracts? A line the author could have worked out from material the run also gets is the finding. Judge a prompt by what its lines do, never by sections it lacks: a short prompt with nothing spare is the target, not a deficient one. **Input**: if no prompt is given (file path or inline text), ask before analyzing — don't assume. Report format: ## Assessment: {Excellent | Good with Minor Issues | Needs Work} **Strengths** — what's working, what the author should preserve. **Issues**: | Issue | Severity | Fix | |-------|----------|-----| | {description} | High / Medium / Low | {concrete recommendation} | **Priority**: the highest-impact change first. **Severity**: - **High** — the prompt actively misbehaves or breaks a contract. Examples: contradiction between two rules that can't both hold; missing the goal entirely; absolute used on a judgment call that observably misfires; the agent declares a need for a tool it doesn't have, or omits a tool it actually uses. - **Medium** — the prompt works but drifts toward known failure modes. Examples: vague directive that produces inconsistent behavior across runs; restat...

Details

Author
doodledood
Repository
doodledood/manifest-dev
Created
7 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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