本文へ移動
cccskills
無料GitHub で公開

asq-writing-style

Use for full-manuscript prose and narrative craft on an Administrative Science Quarterly (ASQ) manuscript — voice, structure, and the storytelling ASQ is known for. Polishes the writing; it does not change the theory or analysis.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.3 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。

Writing Style & Craft (asq-writing-style)

When to trigger

  • The theory and analysis are settled; the prose needs to reach ASQ's craft bar
  • The manuscript is technically correct but flat, jargon-heavy, or hard to follow
  • A process study is written in dead "variance-speak"
  • Reviewers/editors praise the idea but call the writing "dense" or "unclear"

ASQ's craft bar

ASQ is known for superb writing — long-form articles with a strong narrative arc. The best ASQ papers read as compelling intellectual stories, not as lab reports; Weick's (1993, ASQ) Mann Gulch paper is the canonical example of analysis carried by narrative. The journal's guidelines treat the compelling presentation of supporting evidence as one dimension of a submission's quality (verify at journals.sagepub.com/author-instructions/asq), and current editorial communications emphasize curation — selecting and shaping papers that will endure. Craft is a real evaluation criterion here, not a courtesy.

The narrative arc

  • Open with the puzzle. The first page should make a smart reader curious and slightly uncomfortable — the anomaly, not a literature catalog.
  • Build tension, then resolution. The paper is an argument that travels from puzzle → why existing theory fails → your insight → evidence → reframing.
  • Foreground theory throughout. The theoretical thread is visible in every section, not just intro and discussion.
  • Earn the surprise. Set up the prior carefully so the reader feels the reversal when it comes.
  • Close on generativity. End by opening new questions, not by restating findings.

Prose discipline

  • Plain, precise English. Prefer concrete verbs and clear subjects; cut nominalizations ("the operationalization of the conceptualization…").
  • Define jargon once, then use it consistently. Do not stack neologisms.
  • One idea per paragraph, with a topic sentence that carries the argument.
  • Active voice where it aids clarity, especially in qualitative work where the researcher's role matters.
  • Signpost transitions so the reader always knows where they are in the argument.

Process vs. variance voice

  • For process theory, write in process language: events, sequences, becoming, unfolding, feedback. Do not flatten a process into "factor A raised outcome B."
  • For variance theory, be precise about relationships, conditions, and magnitudes — but still narrate why.

Qualitative-specific craft

  • Weave informant voice into the analysis; quotes should advance the argument.
  • Show the field — enough thick description to make the setting vivid and the inference credible — without drowning the theory.
  • Maintain analytic distance: vivid but not journalistic; interpretive but disciplined.

Checklist

  • Opens with the puzzle, not a literature dump
  • A single, traceable theoretical thread runs through every section
  • The surprise is set up so the reader feels the reversal
  • Jargon defined once and used consistently; nominalizations cut
  • One idea per paragraph; topic sentences carry the argument
  • Process papers written in process voice (not variance-speak)
  • Qualitative: informant voice advances the argument; setting is vivid but disciplined
  • Ends on generativity (new questions), not a findings recap

Anti-patterns

  • "Lab-report" prose: mechanical, voiceless, no narrative tension
  • Front-loading the literature so the puzzle never lands
  • Jargon stacking and undefined neologisms
  • Variance-speak imposed on a process phenomenon
  • Quote-dumping in qualitative papers with no analytic threading
  • A discussion that restates results instead of opening questions

Output format

【Narrative arc】puzzle → tension → insight → evidence → generativity (status)
【Theoretical thread】visible throughout? (yes/no)
【Voice】process / variance — matches phenomenon?
【Prose issues fixed】jargon / nominalizations / paragraphing
【Qual craft】informant voice + setting balanced?
【Next step】asq-submission

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。

同じリポジトリのスキル

概要と使いどころ

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

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。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

brycewang-stanford のスキルをすべて見る

このスキルの問題を報告する