Use when an approved `evidence-review` protocol needs to be applied to a candidate pool.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
evidence-review 的 screening 阶段（C2/C3），protocol 已锁定并通过 HUMAN 审批。output/PROTOCOL.md（或 protocol 未通过签字）。Transforms an approved protocol plus candidate pool into an auditable screening log.
Required:
output/PROTOCOL.mdCandidate pool:
papers/papers_raw.jsonlpapers/papers_dedup.jsonlpapers/core_set.csvpapers/screening_log.csvEach row must include at least:
paper_idtitleyearurldecisionreasonreason_codesreviewerdecided_atscripts/run.py should:
It should not invent new protocol rules.
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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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