by smixs · Codex Skill · ★ 73
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Architecture-first skill lifecycle for AI agents. 5 modes: CREATE → EVAL → EDIT → REVIEW → PACKAGE. Integrates Anthropic's eval engine (grader/comparator/analyzer agents, blind A/B, benchmarks) with architecture patterns, TDD baseline, and 5-axis scoring. Not just testing - full design-to-distribution.
| Stars | 73 |
| Forks | 10 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 41.25/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-04 |
| Created | 2026-03-03 |
| Platforms | claude-code, python |
| Est. Tokens | ~7k |
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skill-conductor is Architecture-first skill lifecycle for AI agents. 5 modes: CREATE → EVAL → EDIT → REVIEW → PACKAGE. Integrates Anthropic's eval engine (grader/comparator/analyzer agents, blind A/B, benchmarks) with a. It is categorized as a Codex Skill with 73 GitHub stars.
skill-conductor is primarily written in Python. It covers topics such as agent-skills, ai-agents, anthropic.
You can find installation instructions and usage details in the skill-conductor GitHub repository at github.com/smixs/skill-conductor. The project has 73 stars and 10 forks, indicating an active community.
skill-conductor is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skill-conductor on Agent Skills Hub include awesome-claude-skills, entroly, COG-second-brain. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.