Score an existing reader-facing deliverable and emit a deterministic PASS/FAIL scorecard plus bounded repair plan; use after synthesis, not to rewrite content.
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See how to installReview the instructions the agent will receive before you install.
Runs the final quality gate for a reader-facing deliverable and always writes a PASS/FAIL report.
Primary input depends on the active pipeline contract:
output/DELIVERABLE_SELFLOOP_TODO.mdresearch-brief: output/BRIEF_SCORECARD.md and output/BRIEF_SCORECARD.jsonpaper-review: output/REVIEW_SCORECARD.md and output/REVIEW_SCORECARD.jsonidea-brainstorm: output/IDEA_SCORECARD.md and output/IDEA_SCORECARD.jsonevidence-review: output/EVIDENCE_SCORECARD.md and output/EVIDENCE_SCORECARD.jsonThe gate should dispatch by pipeline contract first:
quality_contract.deliverable_kindOnly fall back to legacy profile-name checks when contract metadata is missing.
scripts/run.py should:
It should not mutate the deliverable itself.
- Status: PASS or - Status: FAILresearch-brief additionally requires valid core-set pointers and the configured score thresholdpaper-review additionally requires the configured score threshold and all critical rubric dimensionsidea-brainstorm additionally requires traceable anchors, actionable lead directions, and the configured score thresholdevidence-review additionally requires clause-linked screening, complete extraction rows, synthesis pointers, and the configured score thresholdNo reviews yet. Tell others what you thought.
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Internal template for creating or refactoring a skill into the repository's reference-first shape. **Trigger**: reference-first template, blueprint skill, create a reusable skill, refactor a script-heavy skill. **Use when**: you need a lean `SKILL.md`, explicit `references/`, machine-readable `assets/`, and a minimal deterministic `run.py`.
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Download a small corpus of open-access arXiv survey/review PDFs about agentic systems and extract text for style learning.
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Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries.
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Curate reader-facing survey tables for the Appendix (clean layout + high information density), using only in-scope evidence and existing citation keys.
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Build a final, machine-readable argument snapshot from current H3 sections and refresh section fingerprints before merge.
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Audit one research Workspace for declared Unit outputs and Pipeline target Artifacts, writing `output/CONTRACT_REPORT.md`; use for mid-Run coverage snapshots or final delivery completeness, not deep provenance integrity.
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