skillrank: Find and Evaluate AI-Agent Skills
Summary
SkillRank is a Rust CLI for discovering, installing, and evaluating skills used by coding agents. Its paired local evaluations compare a skill-enabled run with a control to show changes in success, tokens, time, and cost.
At a glance
- Language
- Rust
- License
- MIT
- Stars
- 0
- Forks
- 0
- Added to OSRepos
- October 4, 2026
- Last analyzed
- October 4, 2026
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Overview
SkillRank helps developers find and manage SKILL.md packages for coding agents, then assess their practical effect instead of relying on popularity or install counts. Its local evaluation harness runs paired trials with and without a skill on the developer's agent and reports changes in success, token use, turns, time, and cost.
The CLI can be used without an account for search, installation, recommendations, and local evaluation. Contributions such as publishing skills and reviews require login. SkillRank also offers MCP integration for Claude Code and Codex, and can run a local registry with a seed catalog.
Key Features
- Search and inspect skills, with filters for stack, agent, and category.
- Install skills with content-hash verification, lockfile tracking, and drift reporting.
- Recommend skills based on detected repository stack.
- Run paired skill-versus-no-skill evaluations on the user's agent and report per-task metric deltas.
- Keep evaluation results separated by trust tier: official, community-reported, and self-reported.
- Register SkillRank tools with Claude Code and Codex through an MCP server.
- Serve a local registry for search, recommendations, and installation without relying on a hosted registry.
- Publish skills and contribute ratings, reviews, and evaluation results with an account.
Use Cases
- A coding-agent user wants to check whether a skill changes task effort or outcomes before adding it to a project.
- A developer wants to discover skills suited to a repository's framework or toolchain.
- A team wants hash-verified skill installation and a record of installed skills in its repositories.
- A skill author wants to publish a package and contribute evaluation results or reviews to the registry.
- A user of Claude Code or Codex wants to search for and manage skills through native agent tools.
Project Facts
- Language: Rust
- License: MIT
- Stars: 0
- Forks: 0
- Topics: none
- Archived: no
Getting Started
Install with the project installer:
curl -fsSL skillrank.dev | sh
Then try skillrank search playwright or skillrank recommend. See the README for evaluation setup, MCP integration, configuration, and build instructions.
Alternatives
- clawhub: ClawHub provides a shared registry and install workflows for OpenClaw skills, while SkillRank focuses on discovering, installing, and evaluating skills across coding-agent runs.
- SkillOpt: SkillOpt iteratively improves skill documents using scored task trajectories; SkillRank measures the effect of enabling a skill against a control run.
- SkillSpector: SkillSpector checks skills for security risks before installation, while SkillRank evaluates their impact on task success, tokens, time, and cost.
Considerations
- Evaluation results depend on the agent, suite, and trial count. The README cautions that results from fewer than five trials per arm are directional, not significant.
- Evaluations run on the user's agent and use task suites with pinned fixture repositories. Cost may be unavailable when an agent or trial does not report it.
- Search and install use a registry over HTTP. A local registry is available; publishing and other contributions require an account.
- The repository's input metadata lists MIT, while the README distinguishes the CLI and core library, which are MIT, from the hosted registry and website, which use Elastic License 2.0. Check component licenses if self-hosting or redistributing those services.
- The repository lists 0 stars and 4 open issues, so public adoption and issue activity are limited indicators of maturity.
Source repository
Open the original repository on GitHub.
Related repositories
Similar repositories that may be relevant next.
prime-agent: Run Self-Improving Agents for Coding Work
October 2, 2026
Prime Agent is a coding and research agent built for long-running tasks, using a persistent Python environment, recursive subagents, and durable working context. It suits developers and researchers who need agents to keep working across sessions.
SwarmLLM: Run Local and Distributed AI Models
October 2, 2026
SwarmLLM runs open AI models on your computer and can pool resources with other computers to run larger models. It also provides OpenAI- and Anthropic-compatible APIs for local apps and agents.
OpenCompany: Coordinate AI Agents to Run a One-Person Business
September 30, 2026
OpenCompany is a Rust-based host for configuring and running companies staffed by coordinated AI agents. It is aimed at solo operators who want to delegate business functions while retaining key decisions, and is explicitly not production-ready.
codeg: Coordinate AI Coding Agents in One Workspace
September 30, 2026
Codeg brings multiple AI coding agents into a shared workspace for conversations, code changes, and delegated tasks. It suits developers who want to compare or coordinate agents across desktop, self-hosted, and Docker setups.