원클릭으로
citation-hygiene
Prepare citation-ready notes for drafting, fact-checking, and legal review.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Prepare citation-ready notes for drafting, fact-checking, and legal review.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | citation-hygiene |
| description | Prepare citation-ready notes for drafting, fact-checking, and legal review. |
| version | 1.0.0 |
Usable output:
Weak output:
Requirements:
Output format:
Claim:
Source:
Exact support:
Quote, if any:
Paraphrase allowed:
Evidence grade:
Risk:
Context: A claim that "Boeing executives knew about MCAS instability before the first crash" needs citation-grade backing before legal review.
input: claim="Boeing executives knew about MCAS instability before the Lion Air crash"
output: Returns citation-ready notes — primary anchor (DOJ 2021 deferred prosecution agreement, paragraphs cited), secondary (Seattle Times investigative series with FOIA'd emails), allegation vs. admission distinction marked (DPA contains admission of misleading FAA, not specific pre-crash internal-knowledge admission), proposed safer phrasing for legal review, handoff to Nancy.
Context: Boundary case: a primary document is paywalled and Wayne cannot quote it.
output: Returns the citation with an access note, proposes a secondary source that summarizes the same paragraph, and asks Delon to budget the paywall fee if the quote is load-bearing for the chapter.
Audit the book-level callback graph that tracks setup → payoff edges across chapters. Verifies every planted anchor has its declared downstream payoff and every payoff still has its upstream plant. Catches orphaned plants and orphaned payoffs. Reads `book/registries/callback-graph.yml`; runs book-wide when any graph chapter is rewritten. Cousin of fair-clue-audit (which covers chapter-internal recognition).
Build a structured responsibility-laundering case file from a historical, political, legal, corporate, war, or AI event.
Turn approved case files into chapter architecture for serious trade nonfiction.
Diagnose a chapter against the 10 reader-experience values in rule 12 (5 core + 5 craft) and build a defect map naming which values fail, with cited prose evidence, and recommending one of the five treatment classes from rule 08. Output is `process/defect-map/<n>-<slug>.md` plus a treatment-class row appended to `book/registries/treatment-classes.yml`.
Audit chapter prose for verbose inline `[CITE:]` markers that violate rule-13's slug-only invariant. Inline `[CITE:]` brackets must carry only card slugs (separated by `;` for multi-source claims); full citation apparatus lives in the source-ledger card and is compile-generated as Chicago NB endnote. Catches the failure mode where citation metadata leaks from card to prose. Cousin to `scan-cite-density.py` (the cheap pattern-level pass); this skill is the deeper read.
Audit the book's cognitive arc — the discriminations and concepts the reader acquires chapter by chapter — against the actual prose. For each discrimination, verifies introduction, consolidation, and application in every required chapter. For each concept, verifies it is named and used. Reads `book/registries/cognitive-arc.yml`.