Meta-Harness Evolverv1.0.0

The harness evolution loop reads current workspace configs, uses a coding-agent proposer to suggest targeted modifications based on historical candidates, evaluates against a 20-scenario benchmark, and logs results. This automation runs nightly via cron, requiring no manual intervention.

After evaluating candidate harnesses, the system selects new promising candidates based on a Pareto frontier of performance and simplicity. This ensures that only the best trade-offs are explored further, balancing quality and maintainability.

The benchmark includes 20 scenarios across memory, code, coordination, research, communication, and quality. Each scenario has a scoring rubric (0-3) to measure the effectiveness of proposed harness changes, enabling quantitative comparison.

While the system can modify core agent files (SOUL.md, IDENTITY.md, etc.), it enforces strict constraints: no changes to credentials, git safety rules, or security-sensitive settings. This prevents dangerous alterations while allowing meaningful evolution.

The proposer logs its reasoning trace for each candidate, allowing future iterations to learn from past decisions. This builds a knowledge base that guides progressively better proposals, embodying the paper's key insight that skill text is the strongest lever.

Offer a service that continuously optimizes OpenClaw agents for enterprises, using the meta-harness evolver as a core component. Generate recurring revenue through subscription-based optimization cycles and performance monitoring.

Leverage the evolution framework to audit and improve clients' existing agent setups, delivering measurable performance gains. Charge for initial setup, customized benchmarks, and ongoing evolution reports.

Create a marketplace for shareable benchmark scenarios and evolution logs, enabling users to contribute and access diverse test cases. License premium benchmark packs and analytics dashboards for deeper insights.