prompt-optimization
prompt-optimization is an LLM evaluation & observability skill for AI agents, published by langwatch in the langwatch repository on GitHub. Skillspace rates prompt-optimization C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a prompt, when they arrive from the workbench's "Optimize this prompt" menu item, or when they want their bot to answer better. Bootstraps a missing dataset or evaluator first.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 3,534
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 95 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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