agent-design-review
agent-design-review is an Agent frameworks & building agents skill for AI agents, published by dcramer in the peated repository on GitHub. Skillspace rates agent-design-review C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Designs, reviews, and iterates on LLM agents and agent-like workflows. Use when asked to "design an agent", "review this agent", "improve our system prompt", "optimize prompts for caching", "improve tool calling", "reduce hallucinated tool calls", "add structured outputs", "decide if this should be multi-agent", "reduce false positives", "tune agent thresholds", or "build evals for this agent". Covers architecture choice, cache-friendly prompt templates, tool and schema design, runtime loops, trust boundaries, and eval-driven iteration.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 96
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
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.