This manual-gated repository provides a versioned copy of the MATTER-604 reference answers, per-task rubrics, Gold fixtures, and evaluator code to trusted third-party benchmark maintainers.

Scores produced from this package are self-hosted MATTER evaluations, not official scores issued by the canonical private evaluator maintained by MatMaster-DP. See ACCESS_POLICY.md for the evidence and reporting contract.

Repository contents

MATTER-604-evaluator-access/
├── README.md
├── ACCESS_POLICY.md
├── LICENSE
├── manifest.json
├── requirements.txt
├── restricted_assets.json
├── score-config.yaml
├── tasks.tsv
├── evaluation/
│   ├── __init__.py
│   ├── config.yaml
│   ├── core/
│   ├── question_bank/
│   ├── scripts/
│   └── validators/
└── .gitattributes

Path	Description
`README.md`	Dataset Card describing the evaluator package, repository layout, scoring components, and access workflow.
`ACCESS_POLICY.md`	Operating and reporting contract for answer isolation, evidence retention, self-hosted evaluation, and Bohr CLI traces.
`LICENSE`	Apache-2.0 license for MATTER-owned content.
`manifest.json`	Machine-readable package identity: 604 tasks, manual-gated release type, evaluator commitment, scoring authority, and resource metadata.
`requirements.txt`	Pinned Python dependencies required by the evaluator and scientific validators.
`restricted_assets.json`	Identity, size, SHA-256, provenance, and acquisition records for six license-controlled scientific inputs.
`score-config.yaml`	Scoring configuration with equal correctness, grounding, and efficiency weights plus the evaluator-LLM runtime settings.
`tasks.tsv`	Ordered index of 604 unique task IDs used to select and align question-bank records.
`evaluation/`	Hidden question bank, reference answers, rubrics, evidence model, scoring engine, validators, and scoring scripts.
`.gitattributes`	Hugging Face repository transport metadata managed by the Hub.

Evaluation package

The evaluation/ tree contains 406 repository files organized as follows:

Component	Files	Description
`evaluation/core/`	15	Evaluator construction, schemas, evidence records, scoring orchestration, LLM utilities, task loading, and score aggregation.
`evaluation/question_bank/`	363	Sixty question-bank YAML files containing 604 unique tasks, their reference-answer fields, 5,288 checklist criteria, and the scientific inputs used by the evaluator.
`evaluation/scripts/`	3	Entry points for devshell scoring, external-baseline scoring, and audited Bohr CLI receipt collection.
`evaluation/validators/`	23	Deterministic checks for structures, compositions, densities, distances, planarity, VASP, ABACUS, GPUMD, GROMACS, DP-GEN, JSON/text artifacts, Bohr CLI operations, and run budgets.
`evaluation/config.yaml`	1	Evaluator defaults and runtime configuration consumed by the scoring engine.
`evaluation/__init__.py`	1	Python package entry point for the evaluation modules.

All 604 tasks contain a scoring checklist. The question bank contains 5,288 criteria across correctness, grounding, and efficiency. Reference-answer fields are populated for 598 tasks; the six safety-refusal tasks encode their expected behaviour through their checklists.

Scoring scripts

evaluation/scripts/baseline/score_baseline_tasks.py
evaluation/scripts/devshell/score_devshell_tasks.py
evaluation/scripts/devshell/bohr_cli_audit.py

score_baseline_tasks.py builds evidence from an external Agent workspace and retained event stream, then evaluates the task criterion by criterion.
score_devshell_tasks.py reads devshell workspaces, summaries, events, and process receipts before producing axis scores and per-criterion reasons.
bohr_cli_audit.py wraps the real bohr executable during solving and writes structured bohr_cli_receipts.jsonl evidence for platform-operation checks.

Scientific validators

The validator collection covers CIF/POSCAR/STRU parsing, composition, density, atomic distances, ordering, molecular crystals, planarity, VASP INCAR, ABACUS inputs, GPUMD run.in, GROMACS topologies, DP-GEN arguments, KPT files, JSON and text outputs, Bohr CLI receipts, artifact budgets, token budgets, and turn budgets.

Runtime dependencies

The evaluator pins ASE, pymatgen, NumPy, Pydantic, PyYAML, JSON Schema, DP-GEN, Molcrys-kit, OpenAI, and Requests in requirements.txt. score-config.yaml uses equal weights for correctness, grounding, and efficiency and configures the evaluator LLM as deepseek-v4-pro with deterministic temperature 0.0.

Bohr CLI tasks

Fifty-three of the 604 tasks are tagged bohr-cli. Their solve environment must contain an authenticated real Bohr CLI and the evaluation audit launcher must preserve bohr_cli_receipts.jsonl. The published three-Agent runs used Node.js 22 and @dptech-corp/bohr-cli@2.5.17. The devshell scorer reads the retained receipts as part of the self-hosted evidence package.

License

MATTER-owned content in this repository is provided under Apache-2.0.

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