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hypothesis-review-pipeline
Run the decomposed review pipeline for a single hypothesis and persist each review stage as a structured artifact.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Run the decomposed review pipeline for a single hypothesis and persist each review stage as a structured artifact.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Run the full Co-Scientist pipeline for one research run.
Evaluate whether a hypothesis newly entered the current top-k set and update the convergence counter deterministically.
Assemble a dashboard-ready snapshot from the canonical state.
Choose exactly one concrete evolution strategy for the active evolution round.
Run the assumption decomposition and deep verification review for a hypothesis.
Run the iterative evolution loop from the current persisted run state until convergence.
| name | hypothesis-review-pipeline |
| description | Run the decomposed review pipeline for a single hypothesis and persist each review stage as a structured artifact. |
Goal:
Inputs:
ResearchPlanMetaReviewHypothesisstate/PIPELINE_STATE.jsonOutputs:
hypotheses/<id>/REVIEW/INITIAL_REVIEW.jsonhypotheses/<id>/REVIEW/FULL_REVIEW.jsonhypotheses/<id>/REVIEW/DEEP_VERIFICATION.jsonhypotheses/<id>/REVIEW/OBSERVATION_REVIEW.jsonhypotheses/<id>/REVIEW/SIMULATION_REVIEW.jsonhypotheses/<id>/REVIEW/REVIEW_SUMMARY.jsonliterature/queries/<query_id>/* when full review or deep verification needs external literature evidencehypotheses/<id>/HYPOTHESIS.jsonstate/PIPELINE_STATE.jsonstate/CURRENT_STAGE.jsonSub-skills:
hypothesis-initial-reviewliterature-searchhypothesis-full-reviewhypothesis-deep-verificationhypothesis-observation-reviewhypothesis-simulation-reviewhypothesis-review-summaryContext Loading:
skills/shared-references/schema-index.md.packages/agent_contracts/review.py before writing any per-stage review artifact under hypotheses/<id>/REVIEW/.packages/agent_contracts/hypothesis.py before updating the embedded review payload inside hypotheses/<id>/HYPOTHESIS.json.packages/agent_contracts/literature.py and skills/shared-references/literature-search-contract.md before dispatching hypothesis-full-review or hypothesis-deep-verification.packages/agent_contracts/pipeline_runtime.py before updating state/PIPELINE_STATE.json or state/CURRENT_STAGE.json.skills/shared-references/codex-reviewer-routing.md before using any optional Codex reviewer subagent route.RUN_POLICY.yaml before dispatching review work so the active review_rigor setting is honored.Execution Contract:
hypotheses/<id>/HYPOTHESIS.json artifact must be updated after every review stage so the embedded review payload stays in sync with the per-stage review files.from tools import sync_hypothesis_review after each stage artifact write. The canonical synchronization helper is implemented in packages/run_artifacts/review_sync.py; do not hand-edit embedded review JSON.from tools import sync_pipeline_stage_artifacts as the canonical paired write surface for entering the Reflection substage.tools.sync_hypothesis_review(run_dir, hypothesis_id) as a hard gate. If it fails, stop the review sequence immediately instead of continuing with later stages.tools.sync_pipeline_stage_artifacts(run_dir, current_phase="Reflection", current_skill="hypothesis-review-pipeline") before starting the review sequence.tools.search_literature(run_dir, request) or an existing matching EvidenceBundleContract before making external literature support claims.Viable evolved hypothesis, Refined from parent, Must outperform parent, Synthesize evolved catalyst, or Benchmark against parent as the substantive content of any completed review artifact.reviewerRoute = local_main_thread in the trace.state/agent_traces/codex/<skill>/<timestamp>.json; the trace is audit evidence and must not replace canonical review artifacts.tools.sync_hypothesis_review and schema validation.review_rigor, run the full review stack for every hypothesis:
hypothesis-full-reviewhypothesis-deep-verificationhypothesis-observation-reviewhypothesis-simulation-reviewreview_rigor may shorten or deepen the reasoning inside those stages, but it must not disable any review artifact.Execution Steps:
skills/shared-references/schema-index.md and skills/shared-references/codex-reviewer-routing.md, then read packages/agent_contracts/review.py, packages/agent_contracts/hypothesis.py, packages/agent_contracts/literature.py, and packages/agent_contracts/pipeline_runtime.py before writing any per-stage review artifact, embedded review state, literature evidence artifact, reviewer trace, or run-level stage artifact.RUN_POLICY.yaml.tools.sync_pipeline_stage_artifacts(run_dir, current_phase="Reflection", current_skill="hypothesis-review-pipeline").hypothesis-initial-review and persist the resulting stage artifact.tools.sync_hypothesis_review(run_dir, hypothesis_id) to synchronize review.initial_review back into hypotheses/<id>/HYPOTHESIS.json. If sync fails, stop here and repair the artifact instead of continuing.review_rigor, then run the full remaining atomic review stack for the hypothesis. When hypothesis-full-review or hypothesis-deep-verification needs external literature evidence, require those skills to call tools.search_literature(run_dir, request) or consume an existing matching evidence bundle.tools.sync_hypothesis_review(run_dir, hypothesis_id) again so the standalone stage artifact and aggregate hypothesis artifact remain consistent. If sync fails, stop before the next stage.hypothesis-review-summary after the required review stages finish.python -m tools.validation.contract_validation <run_dir> --skill hypothesis-review-pipeline. If validation fails, stop and repair the review bundle before declaring completion or returning control.Completion Rule:
hypotheses/<id>/HYPOTHESIS.json matches those stage artifacts, and the resulting files validate for downstream routing.