Add MiniMax Code Harbor evaluation profile - #2
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Summary
mcodeadapterReproducibility pins
0.22.0@minimax-ai/code0.2.722.23.2(official Linux x64 archive SHA-256 verified)sha256:7d7bdc1cbedad549fc1140404bd4dc45e5fd0ea7c4186773687d177ad3a0699a435ee89ec2f2e2289f33b0da4f992f0b7b7266b9Every restored MCode checkpoint recomputes and compares the public-task tree, runnable Terminal-Bench and DeepSWE trees, MCode bundle, adapter source, and DeepSWE HEAD before a trial can run. An existing run ID also rejects changes to the checkpoint, harness/version, provider/model routes, timeout, or command identities.
Validation
skills/frontierharness-eval/tests/test-minimax-code.shbash -n skills/frontierharness-eval/scripts/*.sh skills/frontierharness-eval/tests/*.shnode --check skills/frontierharness-eval/scripts/*.mjsuvx ruff check skills/frontierharness-eval/agents/frontierharness_mcode.pyquick_validate.py0.22.0resolution and full export of the pinned Terminal-Bench digest; verified all 21 selected Terminal-Bench and 9 DeepSWE overlays load from the resulting local task trees--print-configvalidationI did not run a real Runta/Kimi K3 task or the full 30-task sweep from this environment: it has no Runta/provider credentials and its Docker daemon is unavailable. This PR adds the reproducible integration workflow, not benchmark result claims.
Stack
This PR is intentionally based on and targets #1 (
feat/third-part-harness), which introduces the agent-neutral evaluation workflow that this MiniMax Code profile extends.