auto-optimize-prompt
SolidIteratively auto-optimize a prompt until no issues remain. Uses review-prompt in a loop, asks user for ambiguities, applies fixes via prompt-engineering skill. Runs until converged.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- doodledood
- Repository
- doodledood/manifest-dev
- Created
- 7 months ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
prompt-optimizer
Use when asked to improve, optimize, rewrite, tune, or port a prompt, skill, or tool description, to build prompt evals, or to audit prompt text for dated instructions. Optimize mode returns a shorter prompt validated on holdout cases; audit mode returns a confidence-ordered findings report and a proposed diff, and applies nothing.
prompt-optimizer-loop
Use this skill when the user wants to improve, tune, or optimize an existing prompt or system instruction — phrasings like "improve this prompt", "my prompt works 80% of the time", "optimize my system prompt", "make this prompt more reliable", "tune this instruction". Runs an interactive optimization loop, one mutation per round, scored against a locked binary checklist, keeping only changes that improve the score. Requires three inputs from the user — the target prompt, 2-3 realistic test inputs, and 3-6 binary quality checks (offer to help draft checks if missing). Do NOT use for writing a brand-new prompt from scratch, or for one-off output fixes where the prompt itself isn't the problem.
prompt-optimizer
Optimizes prompts through an iterative Claude-GPT review process. Use when the user wants to optimize, improve, or refine a prompt. Supports automated review via the Codex CLI or manual GPT handoff.