SkillBench MCP Server
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SkillBench MCP Server
A zero-dependency harness that runs held-out coding tasks with and without a skill file, then reports behavior deltas and variance. Packaged as a mcp server so users can adopt it quickly.
Why This Exists
Skill repos are getting daily attention, but the ecosystem has almost no proof that skills improve agent behavior.
Related MCP server: cold-run
One-Day MVP
YAML/JSON task fixtures, paired runs, transcript diffing, pass/fail metrics, and a Markdown report.; one local MCP tool, install docs, example agent transcript.
What It Does Today
Loads a small JSON task or project description.
Checks whether the required fields and examples are present.
Produces a JSON or Markdown readiness report.
Ships with tests and a CI workflow so the repo is immediately verifiable.
Install
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -e .Run
python -m skillbench_mcp_server.cli --input examples/sample_input.json --format markdownValidate
python -m unittest discover -s testsValidation Query
agent skills eval
Comparable Repos
darkrishabh/agent-skills-eval: 656 stars - A test runner for agentskills.io-style AI agent skills
caohaotiantian/agent-skills-eval: 8 stars -
sasa-fajkovic/agents-skill-eval: 4 stars - agents-skill-eval.com
Launch Angle
show the same workflow from Claude Code/Codex/Cursor where possible
Publishing Gate
must disclose permissions and local data access
Working demo or executable artifact.
Clear examples and tests.
Honest limitations.
No fake stars, duplicate repos, or automated engagement.
Status
Generated by RepoForge Radar. Treat this as a starting implementation, not a finished product.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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This server cannot be deployed
Maintenance
Related MCP Connectors
Build and run team decision simulations for training and assessment from a chat description.
Simulation, evaluation and monitoring for voice agents.
Read-only, deterministic AI triage and readiness tools implementing Sophon's published rubrics.
Hand tasks, bugs and finished work to AI coding agents, and get back a write-up with evidence.
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