Hypothesis review pipeline

hypothesis-review-pipeline

Goal:

• Run the decomposed review pipeline for a single hypothesis and persist each review stage as a structured artifact.

Inputs:

• ResearchPlan
• MetaReview
• Hypothesis
• optional resume context from state/PIPELINE_STATE.json

Outputs:

• hypotheses/<id>/REVIEW/INITIAL_REVIEW.json
• hypotheses/<id>/REVIEW/FULL_REVIEW.json
• hypotheses/<id>/REVIEW/DEEP_VERIFICATION.json
• hypotheses/<id>/REVIEW/OBSERVATION_REVIEW.json
• hypotheses/<id>/REVIEW/SIMULATION_REVIEW.json
• hypotheses/<id>/REVIEW/REVIEW_SUMMARY.json
• literature/queries/<query_id>/* when full review or deep verification needs external literature evidence
• updated hypotheses/<id>/HYPOTHESIS.json
• updated state/PIPELINE_STATE.json
• updated state/CURRENT_STAGE.json

Sub-skills:

• hypothesis-initial-review
• literature-search
• hypothesis-full-review
• hypothesis-deep-verification
• hypothesis-observation-review
• hypothesis-simulation-review
• hypothesis-review-summary

Context Loading:

• Open skills/shared-references/schema-index.md.
• Read packages/agent_contracts/review.py before writing any per-stage review artifact under hypotheses/<id>/REVIEW/.
• Read packages/agent_contracts/hypothesis.py before updating the embedded review payload inside hypotheses/<id>/HYPOTHESIS.json.
• Read packages/agent_contracts/literature.py and skills/shared-references/literature-search-contract.md before dispatching hypothesis-full-review or hypothesis-deep-verification.
• Read packages/agent_contracts/pipeline_runtime.py before updating state/PIPELINE_STATE.json or state/CURRENT_STAGE.json.
• Read skills/shared-references/codex-reviewer-routing.md before using any optional Codex reviewer subagent route.
• Read RUN_POLICY.yaml before dispatching review work so the active review_rigor setting is honored.
• Read the current hypothesis, research plan, and any optional run-level review guidance before starting the stage sequence.

Execution Contract:

• This pipeline skill does not own hidden prompt templates.
• It orchestrates atomic review skills so the runtime can trace each review stage independently.
• Downstream atomic review skills remain responsible for the exact field-level contents of each standalone review artifact.
• The canonical 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.
• Use 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.
• Use from tools import sync_pipeline_stage_artifacts as the canonical paired write surface for entering the Reflection substage.
• Treat 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.
• On entry, call tools.sync_pipeline_stage_artifacts(run_dir, current_phase="Reflection", current_skill="hypothesis-review-pipeline") before starting the review sequence.
• When consumed by a host agent, validate both the embedded hypothesis review payload and the per-stage review artifacts. If validation fails, stop and repair the review bundle before running the next stage or returning control.
• Full review and deep verification must use tools.search_literature(run_dir, request) or an existing matching EvidenceBundleContract before making external literature support claims.
• The review pipeline must not accept prompt-invented paper metadata or model-memory citations as formal evidence.
• The review pipeline must not accept empty completed review artifacts. A completed or passing stage must contain concrete, hypothesis-specific findings that downstream evolution and ranking can use.
• Do not use placeholder review phrases such as 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.
• Codex reviewer subagents are optional. If unavailable, run the same review contract in the main thread and record reviewerRoute = local_main_thread in the trace.
• If a Codex reviewer subagent is used, record state/agent_traces/codex/<skill>/<timestamp>.json; the trace is audit evidence and must not replace canonical review artifacts.
• Reviewer subagents must not write deterministic mechanics artifacts or bypass tools.sync_hypothesis_review and schema validation.
• Regardless of review_rigor, run the full review stack for every hypothesis:
  • hypothesis-full-review
  • hypothesis-deep-verification
  • hypothesis-observation-review
  • hypothesis-simulation-review
• review_rigor may shorten or deepen the reasoning inside those stages, but it must not disable any review artifact.

Execution Steps:

1. Open 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.
2. Read the research plan, current hypothesis, optional meta-review guidance, and active RUN_POLICY.yaml.
3. Before dispatching atomic review work, call tools.sync_pipeline_stage_artifacts(run_dir, current_phase="Reflection", current_skill="hypothesis-review-pipeline").
4. Run hypothesis-initial-review and persist the resulting stage artifact.
5. Immediately call 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.
6. Determine the required reasoning depth from 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.
7. After each later review stage, call 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.
8. Run hypothesis-review-summary after the required review stages finish.
9. Run 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:

• This skill is complete only when all review-stage artifacts exist, the embedded review payload in hypotheses/<id>/HYPOTHESIS.json matches those stage artifacts, and the resulting files validate for downstream routing.