by fastxyz · MCP Server · ★ 58
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
skill-optimizer Docker workbench and Agent Skill for running deterministic evals against agent skills. Use this repo in two ways: Install the skill/plugin into your agent so it can author and debug eval suites. Run the local CLI to execute cases and suites in Docker against OpenRouter models. Installation Installation differs by agent. The canonical skill is ; every plugin manifest points at that same file. Claude Code Register this repository as a Claude Code plugin marketplace: Then install the plugin: OpenAI Codex CLI Register this repository as a Codex plugin marketplace: Then open the plugin search interface: Select and install it. OpenAI Codex App In the Codex app, open Plugins from the sidebar, search for , and install it from the Coding section. If it is not listed, install it from Codex CLI first: Cursor Install the skill with the open skills CLI: Cursor can also import the skill from GitHub via Settings - Rules - Project Rules - Add Rule - Remote Rule (Github). The Cursor plugi
| Stars | 58 |
| Forks | 9 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71.7118989859558/100 |
| Open Issues | 13 |
| Last Updated | 2026-05-28 |
| Created | 2026-03-06 |
| Platforms | cli, mcp, node |
| Est. Tokens | ~150k |
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skill-optimizer is Benchmark, evaluate, and optimize skills to ensure reliable performance across all LLMs. It is categorized as a MCP Server with 58 GitHub stars.
skill-optimizer is primarily written in TypeScript. It covers topics such as ai, ai-agent, ai-skill.
You can find installation instructions and usage details in the skill-optimizer GitHub repository at github.com/fastxyz/skill-optimizer. The project has 58 stars and 9 forks, indicating an active community.
skill-optimizer is released under the MIT license, making it free to use and modify according to the license terms.
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