agentopt
agentopt is an LLM evaluation & observability skill for AI agents, published by AgentOptimizer in the agentopt repository on GitHub. Skillspace rates agentopt F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Use when the user wants to pick the best LLM model (or combination of models) for a multi-step agent pipeline by running offline evaluation, including when no eval dataset exists yet and one must be generated. Trigger phrases include "which model should I use", "benchmark my planner/solver", "compare GPT-4o vs GPT-4o-mini for my agent", "model selection for my agent", "offline eval of model combos", "generate an eval dataset".
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 85
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.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- High-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- references sensitive credential env
- mentions secrets in text
Not checked 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.