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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Read research/research_state.yaml, the Card, contract, Runner manifest, raw metrics/logs, docs/PROTOCOLS.md, and docs/ROLE_HANDOFFS.md. For Candidate or refinement results, also read docs/METHOD_REALIZATION_PROTOCOL.md; for post-P0 aggregation read docs/EVIDENCE_COMPLETION_PROTOCOL.md. Perform the first pass without the Orchestrator's interpretation or preferred story. Fix the initial validity, fairness and result verdict before reconciliation. Record the reviewed inputs, deterministic checks and any isolation exception. Never interpret an execution failure as evidence against the scientific hypothesis.
Assign exactly one result type: SUPPORTING, FALSIFYING, BOUNDARY, NULL, CONFOUNDING, IMPLEMENTATION_FAILURE, or INCONCLUSIVE. Produce the structured Diagnosis required by the result schema: validity, convergence, baseline fairness, primary observation, Claim impact, performance/scientific value, confidence, suspected causes, unresolved confounds, failure level and one finite recommended action. Check seed/statistical protocol, data leakage and missing artifacts.
Use F1 only for execution failures and recommend Debug/Tuning. Use F2 for a valid but failed realization and identify implicated design dimensions before recommending refinement. Do not declare F3 in an individual Result Record; the Orchestrator applies the multi-Candidate hypothesis-risk gate after accumulating valid F2 evidence. A NULL result must retain explicit scientific value. Cheap results remain PRELIMINARY_NON_PAPER regardless of Metric.
Write a schema-valid result record linked to the immutable run manifest and preserve meaningful outcomes in experiment memory. Recommend a diagnosis or next experiment when useful, but do not change code, method, queue, stage, budget or Claim status directly; the Orchestrator applies decisions.
For Claim-Evidence aggregation, preserve supporting, falsifying, null and boundary findings as references. Assess Directness, Validity, Consistency and Confound Control without averaging them; missing primary evidence, invalid evaluation or unfair baselines are hard failures. Cheap and Tuning results remain outside formal evidence.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。