Meta Harness Model Card
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Meta Harness Model Card
| Field | Value |
|---|---|
| Repository | SuperagenticAI/metaharness |
| Category | Benchmark-Driven Harness Evolution Toolkit |
| Stars / forks snapshot | 102 / 11 |
| Language | Python |
| License | Repository LICENSE file |
| Raw capture | raw-github/superagenticai_metaharness.md |
| Updated by | hourly public metadata update, 2026-05-26 10:04 +0800 |
1. Role in Self Evolve
Meta Harness is a benchmark-driven outer loop for coding-agent harness optimization, with reproducible candidate ledgers and run evidence. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
propose harness change -> run benchmark matrix -> compare score/runtime/cost -> keep best candidate -> persist ledger
3. Evidence Path
web-observed GitHub page showed 102 stars, 11 forks, 23 commits, and README language for Codex-first benchmark loops, proposal/evaluate/keep harness iterations, candidate ledgers, write-scope controls, and experiment matrix support. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Benchmark-Driven Harness Evolution Toolkit: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.