tool-selection-strategy
tool-selection-strategy is an Agent behaviour & coding discipline skill for AI agents, published by aiming-lab in the MetaClaw repository on GitHub. Skillspace rates tool-selection-strategy D (67/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when deciding which tools to call in an agentic workflow. Always choose the minimal, most direct tool for each step and avoid redundant or speculative tool calls.
- Grade
- D
- Quality
- 67 / 100
- Safety
- Passed
- GitHub stars
- 3,495
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 98 / 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
Also published in 1 other repo
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