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Add Meta-Harness recipe with a full candidate store - #80
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Meta-Harness (arXiv 2603.28052) gives its proposer filesystem access to every prior candidate's code, scores, and execution traces. The new recipe reproduces that loop under the frozen evaluator: - rollout/meta_harness replays the selected parent like parent_evaluation and builds rollout/candidates/: an index of every candidate with its score, status, handoff, and diffs against its parent and the seed, plus a per-task frontier. Each certified candidate's evaluation is replayed once and later generations point back to it. - mutate/meta_harness carries the reference proposer's rules: one falsifiable mechanism per candidate, read traces across candidates, no task-specific hints, and a handoff note later proposers read. - The certified-replay helpers move from parent_evaluation into library/rollout/_support/certified_replay.py so both operators share the same digest-verified path; parent_evaluation behaviour is unchanged. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0146TTyeMc3Gx6mqsYeGG7vM
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- 🪄 Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @library/rollout/meta_harness.py:
- Around line 204-207: Update the replay logic around the genid-in-prior branch
to reuse prior cases, summary, and per_task only when genid is certified and its
stored artifact digest matches the current row artifact digest. Store the digest
on entries created by both parent and fresh-replay paths so uncertified
candidates or candidates with changed artifacts are replayed anew.
- Around line 208-223: In the certified non-parent candidate branch that calls
replay_certified_cases, catch SystemExit, record its message in that candidate’s
index entry as replay_error, and continue processing other candidates. Keep
writing cases and appending to replayed only when replay succeeds; leave the
selected-parent replay strict.
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📒 Files selected for processing: 29
README.mdREADME.zh-CN.mddocs/QUICKSTART.mddocs/concepts/design.mddocs/reference/operators/mutate.mddocs/reference/operators/rollout.mdlibrary/README.mdlibrary/mutate/meta_harness.pylibrary/rollout/_support/__init__.pylibrary/rollout/_support/certified_replay.pylibrary/rollout/meta_harness.pylibrary/rollout/parent_evaluation.pyrecipes/README.mdrecipes/meta_harness/README.mdrecipes/meta_harness/evolve.yamlscripts/run_recipe_demo.shscripts/setup_terminal_bench.shtests/conftest.pytests/fixtures/normalized_recipe_operator_configs.jsontests/test_evaluation_replay_rollout.pytests/test_m0_init.pytests/test_meta_harness.pytests/test_phase_e_recipes.pytests/test_phase_f_init_binding.pytests/test_recipe_composition.pytests/test_recipe_full_cycle.pytests/test_recipe_inventory.pytests/test_release_artifact.pytests/test_runtime_recipe_conformance.py
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…d best score Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0146TTyeMc3Gx6mqsYeGG7vM
… the Meta-Harness store Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0146TTyeMc3Gx6mqsYeGG7vM
Requested by ye siyu · project thread
Before: RSIHub had no Meta-Harness recipe, though recent harness-evolution papers (VERSE, SIFT and others) use Meta-Harness (arXiv 2603.28052) as their most common baseline. The mutation agent only saw the selected parent's traces, the last 8 attempts and the latest accepted diff.
After:
evolve init --recipe meta_harnessruns a Meta-Harness search on the same MiniSWE × Terminal-Bench 2.0 setup as the AHE and HyperAgents recipes. Each generation, the proposer gets a candidate store listing every prior candidate with its score, status, handoff note, diffs against its parent and the seed, and replayed certified traces, plus a per-task frontier.How:
library/rollout/meta_harness.pyreplays the selected parent exactly likeparent_evaluation, then writesrollout/candidates/{index.json,index.md,frontier.json}. Each certified candidate's evaluation is replayed once, in the first generation after it is certified; later generations point back to that replay rather than copying traces again. Uncertified candidates are listed with code and status only.library/mutate/meta_harness.pycarries the reference proposer's rules: one falsifiable mechanism per candidate, read failed and successful traces across candidates, no task-specific hints, and aHYPOTHESIS / CHANGES / PREDICTION / EVIDENCEhandoff that later proposers see in the index.parent_evaluation.pyintolibrary/rollout/_support/certified_replay.py, so both operators share one digest-verified path.parent_evaluationbehaviour is unchanged and its tests pass; one test now patches the helper module where_artifact_sourceslives.greedyselect,trace_browseranalyze, Codex gpt-5.4 xhigh proposer (same as the other recipes, for comparability),parent_eligiblegate,target/**surface. Differences from the reference implementation are listed inrecipes/meta_harness/README.md.Validation:
ruff check,ruff format --check,ty check: clean.test_agent_runner.py::test_run_mutate_timeout_kills_command_group, also fails on unmodifiedmainin this container.test_recipe_full_cycle.py[meta_harness]with--run-slow: passed. I also continued that offline workspace to 3 generations and confirmed the store indexes all candidates and replays a non-parent candidate once.test_release_artifact.pyagainst a freshuv build: passed.🤖 Generated with Claude Code
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