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evidence-draft

Create per-subsection evidence packs (NO PROSE): claim candidates, concrete comparisons, evaluation protocol, limitations, plus citation-backed evidence snippets with provenance.

インストール方法を見る

含まれるファイル(11)

  • SKILL.md4.9 KB
  • assets/evidence_pack_schema.json1.4 KB
  • assets/evidence_policy.json3.6 KB
  • assets/source_text_hygiene.json10.3 KB
  • references/block_vs_downgrade.md709 B
  • references/evaluation_anchor_rules.md702 B
  • references/evidence_quality_policy.md894 B
  • references/examples_sparse_evidence.md1.2 KB
  • references/overview.md992 B
  • references/source_text_hygiene.md2.5 KB
  • scripts/run.py71.9 KB

SKILL.md(原文)

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。

Evidence Draft

Triggers & routing

  • Trigger: evidence draft, evidence pack, claim candidates, concrete comparisons, evidence snippets, provenance, 证据草稿, 证据包, 可引用事实.

Build deterministic outline/evidence_drafts.jsonl packs from briefs + notes + optional evidence bindings.

Compatibility mode is active: this migration preserves the existing JSONL contract while moving evidence-quality policy, sparse-evidence routing, and evaluation-anchor rules into references/ and assets/.

Load Order

Always read:

  • references/overview.md
  • references/evidence_quality_policy.md

Read by task:

  • references/block_vs_downgrade.md when deciding whether thin evidence should block drafting or only downgrade claim strength
  • references/evaluation_anchor_rules.md when evaluation tokens, protocol context, or numeric claims are weak
  • references/examples_sparse_evidence.md for evidence-thin pack calibration
  • references/source_text_hygiene.md when paper self-narration or generic result wrappers are leaking into pack snippets / claim candidates

Machine-readable assets:

  • assets/evidence_pack_schema.json
  • assets/evidence_policy.json
  • assets/source_text_hygiene.json
  • repo-wide assets/limitation-signals.json — shared polarity rules that keep resolved failures and positive improvements out of limitation slots

Inputs

Required:

  • outline/subsection_briefs.jsonl
  • papers/paper_notes.jsonl
  • citations/ref.bib

Optional but recommended:

  • papers/evidence_bank.jsonl
  • outline/evidence_bindings.jsonl

Outputs

Keep the current output contract:

  • outline/evidence_drafts.jsonl
  • optional human-readable mirrors under outline/evidence_drafts/

Script Boundary

Use scripts/run.py only for:

  • deterministic joins across briefs / notes / evidence bank / bindings
  • snippet extraction and provenance assembly
  • policy-driven blocking_missing / downgrade_signals / verify_fields materialization
  • pack validation and Markdown mirror generation

Do not treat run.py as the place for:

  • filler bullets that make thin evidence look complete
  • hidden sparse-evidence judgment that is not inspectable from references/ / assets/
  • reader-facing narrative prose

Output Shape Rules

Keep these stable:

  • preserve the existing top-level pack fields already used by downstream survey pipelines
  • claim_candidates must remain snippet-derived
  • concrete_comparisons must remain genuinely two-sided; if one cluster has no usable highlight, drop the card and surface thin evidence upstream instead of fabricating an A-vs-B contrast
  • snippet sampling should stay cluster-aware: when a subsection has explicit clusters, evidence selection should avoid collapsing onto one route just because its abstracts contain louder result sentences
  • sparse evidence should surface as explicit blockers / downgrade signals / verify fields, not filler bullets
  • citation keys must remain constrained to citations/ref.bib

Compatibility Notes

Current mode is reference-first with deterministic compatibility:

  • assets/evidence_policy.json defines pack thresholds and sparse-evidence routing
  • assets/evidence_pack_schema.json documents/validates the stable pack shape
  • assets/source_text_hygiene.json owns this Skill's wrapper cleanup, while the repo-wide assets/limitation-signals.json owns limitation polarity across paper-notes, evidence-draft, and writer-context-pack
  • scripts/run.py still materializes the existing JSONL + Markdown outputs, but no longer pads sparse sections with generic caution prose

Quick Start

  • uv run python .codex/skills/evidence-draft/scripts/run.py --workspace <workspace>

Execution Notes

When running in compatibility mode, scripts/run.py currently reads:

  • outline/subsection_briefs.jsonl
  • papers/paper_notes.jsonl
  • citations/ref.bib
  • optionally papers/evidence_bank.jsonl and outline/evidence_bindings.jsonl
  • assets/evidence_policy.json and assets/evidence_pack_schema.json

Script

Quick Start

  • uv run python .codex/skills/evidence-draft/scripts/run.py --workspace <workspace>

All Options

  • --workspace <dir>
  • --unit-id <id>
  • --inputs <path1;path2>
  • --outputs <path1;path2>
  • --checkpoint <C*>

Examples

  • uv run python .codex/skills/evidence-draft/scripts/run.py --workspace <workspace>

Troubleshooting

  • If packs look complete despite thin evidence, inspect assets/evidence_policy.json and references/block_vs_downgrade.md before changing Python.
  • If evaluation bullets are generic, inspect references/evaluation_anchor_rules.md and the policy asset.
  • If claims are strong but evidence is abstract/title-only, downgrade via downgrade_signals and verify_fields rather than adding narrative caveats.

レビュー

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。

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概要と使いどころ

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`.

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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

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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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

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.

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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

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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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

Build a final, machine-readable argument snapshot from current H3 sections and refresh section fingerprints before merge.

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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

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.

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。

WILLOSCAR/research-units-pipeline-skills5132026年10月5日 更新

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