Optimizes an agent's harness (prompts, tools, memory, skills, subagents) on unseen tasks through recursive Propose–Probe–Compose refinement, for researchers benchmarking agents.
- Access
- CLI
- Auth
- None
- Skills
- 4
Skills
Task-Level Recursion
Proposes harness edits, probes their effects on the same task, and composes a refined harness without ground-truth feedback.
Harnessing-Level Recursion
Updates a persistent improvement harness with adopted harnesses and lessons from each task to guide later refinement.
Parallel and Sequential Recursion
Explores K candidate harnesses in parallel or refines one harness through K successive steps.
Benchmark Runs
Sets up, runs, judges, and reports JobBench, LAB, and WorkBuddy-Bench tasks with OpenCode or Codex executors.
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