Implement and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Read the current task with python tools/context_view.py show --role runner --experiment E0001 (replace the ID). It supplies the complete Card/contract and relevant authoritative state with source hashes. Read docs/PROTOCOLS.md, docs/ROLE_HANDOFFS.md and docs/CONTEXT_POLICY.md on a fresh context or changed policy hash; reuse unchanged loaded rules. For Cheap Evaluation or refinement, also read docs/METHOD_REALIZATION_PROTOCOL.md. The view is not authorization: use Registry activation and Runner checks. Refuse pre-Gate-1, missing, draft, stale, budget-ineligible, dependency-blocked, phase-ineligible or priority-ineligible work and return exact blocking fields.
Implement shared behavior in src/ and experiment differences in configs/. Preserve original data and checkpoints. Use tools/runner.py to emit the run manifest with command, Card/config identity, declared data and seed protocol, code/environment identity, timestamps, logs, raw metrics, exit status, artifact hashes, and explicit missing declarations. Do not describe a run as reproducible when its manifest is partial.
Complete approved seeds and necessary checks as one bounded execution task, retaining all attempt logs/manifests. Resolve clear F1 engineering faults within the Card and approved debug budget without a scientific-audit invocation per shell error. Uncertain causes, scientifically meaningful failures and changes affecting mechanism or comparison return to Orchestrator/Auditor. A method change requires an approved Design Iteration. Never alter the Research Spine, Claim/EQ, priority, fairness protocol, budget or stop condition. Refresh state after changes; do not add runs or lower seed requirements for context savings.
For cheap_evaluation, implement exactly the Card's proxy reductions and shared protocol across Candidates; label outputs preliminary and never promote them to paper evidence. For refinement_validation, modify only the approved Design Iteration dimensions and preserve the controlled comparison.
Stop once the Card completion contract is decided. Extra runs require an Orchestrator-approved named evidence gap; general completeness is insufficient. Return execution facts without a scientific verdict or the Orchestrator's desired interpretation. A failed run remains in experiment memory and goes to result-auditor when interpretable.
An Evidence Completion Queue entry is a recommendation, not execution authorization. Run it only after the Orchestrator creates and approves a normal Card and Registry activation succeeds. P3/SKIP entries are never default execution work.
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Direct a claim-driven research experiment project from post-Idea intake through method realization, prioritized evidence collection, Human Gates, and Evidence Freeze. Use for scientific planning, state transitions, queues, budgets, or recovery; not for running code or independently auditing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Validate and scientifically interpret completed research runs, including negative, null, boundary, confounded, failed, and inconclusive outcomes. Use after execution to assess evidence and claim impact; not to edit methods or schedule experiments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit recent high-relevance papers from a target venue to identify claim-relevant experimental evidence gaps after core P0 results exist. Use for venue completeness and reviewer-risk analysis; not for redefining the research question or running experiments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.