Agent Harness Leaderboard

Agent Harnesses

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Name	Stars	Completion	Velocity	Community	Score
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Skill Frameworks

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Name	Stars	Completion	Velocity	Community	Score
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MCP Ecosystem

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Name	Stars	Completion	Velocity	Community	Score
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How Rankings Are Calculated

Scores are computed across five dimensions, weighted to reflect both objective (GitHub activity, release cadence) and subjective (community sentiment, ecosystem health) signals.

Community Scale

35%

GitHub stars, forks, and watchers — log-normalized to prevent superstars from dominating.

Velocity

25%

Recent release activity, commit cadence, and contributor count over the last 90 days.

Ecosystem Health

20%

License, open issue hygiene, documentation quality, and multi-model support signal.

Sentiment

10%

Community sentiment from Reddit (r/ClaudeAI, r/LocalLLaMA, r/ArtificialIntelligence) and Hacker News — refreshed daily.

Benchmarks

10%

SWE-bench, ClawBench, and Terminal-Bench scores where available. Weighted seed-adjusted variance.

Methodology Notes

Normalization: All raw metrics are log-transformed and min-max normalized to [0, 100] within each category (harnesses, skills, MCP). This means scores are relative to peers, not absolute.
Proprietary Entities: Tools without public GitHub repos (e.g., GitHub Copilot, Kimi Code CLI) are listed with estimated scores based on available public signals. Their scores are marked with a †.
Benchmark Sparsity: Many agents lack published benchmark results. Entities with verified benchmark data receive a bonus in the Benchmarks dimension. Entities without benchmarks score 0 in this dimension.
Refresh Cadence: Reddit signals are updated daily via cron. GitHub data is refreshed weekly. A full entity sweep (new entrants, retired tools) runs monthly.
Seed-Aware Variance: Inspired by ClawBench's finding that 47% of performance variance is seed noise, scores carry confidence intervals. Higher signal-to-noise ratio = more trustworthy ranking.
Open Source: This project is fully open source. Contributions welcome — submit new entities, fix scoring weights, or improve the UI.

Data Sources

Source	Data	Frequency
GitHub API	Stars, forks, releases, contributors	Weekly
Reddit Search	Mentions, sentiment analysis	Daily
Hacker News	Discussion threads, upvote ratio	Daily
SWE-Bench	Pass rates by agent	Monthly
ClawBench	Task completion, trajectory, safety	Monthly
Terminal-Bench	CLI task completion rates	Monthly