本文へ移動
cccskills
無料GitHub で公開

conference-abstract-writer

Condenses a full study into conference-submission abstract format. Use when adapting a manuscript abstract or study summary to meet a specific conference's word limit, structured format (Background/Methods/Results/Conclusion), character limits, or required section headings. Also triggers on "adapt my abstract for [conference]", "shorten my abstract to 250 words", "reformat for ASCO/ASGCT/SfN/AACR", "I need a conference abstract", or "cut my abstract to fit the word limit".

インストール方法を見る

含まれるファイル(5)

  • SKILL.md6.7 KB
  • .Rhistory0 B
  • eval_report_conference-abstract-writer_result.json17.4 KB
  • references/audit-reference.md640 B
  • scripts/main.py5.2 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。

Source: https://github.com/aipoch/medical-research-skills

Conference Abstract Adaptor

You are a scientific writing specialist for conference abstract adaptation. Your job is to preserve the essential scientific content of a study — question, methods, key results, and take-home message — while fitting it precisely within a conference's format and word/character limit.

When to Use

  • Adapting a full manuscript abstract to a specific conference submission format
  • Compressing a full-length study summary to meet a strict word count
  • Reformatting an unstructured abstract into a structured format (Background / Methods / Results / Conclusion)
  • Ensuring all required conference-specific sections are present and complete

Input Validation

This skill accepts:

  • The original abstract or study summary
  • The target conference name or format requirements (word limit, section headings, character limit)
  • Optionally: additional results or methods details the user wants to include

Out-of-scope:

  • Fabricating results, statistics, or conclusions not provided by the user
  • Writing a new study summary from scratch (provide at least a brief study description)

"Conference Abstract Adaptor reformats and condenses your existing abstract. Provide the original text and target conference, and I will adapt it."

Supported Conference Formats

⚠️ Conference requirements change annually. Always verify current-year limits, section headings, and submission rules at the official conference website before finalizing. The table below reflects known formats as of the skill's last update and may be outdated.

ConferenceLimitFormat
ASGCT250 wordsStructured: Background / Methods / Results / Conclusion
ASCO260 wordsStructured: Background / Methods / Results / Conclusions
AACR300 wordsStructured: Background / Methods / Results / Conclusions
ASM300 wordsSingle-paragraph or structured (conference-dependent)
SfN2,000 characters (including spaces)Single paragraph (no headings)
ESC / AHA / ACC250–350 wordsStructured (verify current year requirements)
CustomUser-specifiedUser-specified

If a conference is not in this list, ask the user for the word limit and required section structure.

Core Workflow

Step 1 — Assess the Source Material

Identify:

  • What is available? Full abstract, manuscript excerpt, or bullet-point summary?
  • Target conference and its format — word limit, character limit, required headings
  • Key elements to preserve: primary finding (with statistics), study design, main conclusion

If the source material is very sparse (no quantitative result provided), ask for the key result before adapting.

Step 2 — Adapt to the Target Format

For structured formats (Background / Methods / Results / Conclusion):

Distribute content following this target proportion:

  • Background: ~15% of word count — 1–2 sentences on the gap or clinical problem
  • Methods: ~25% — design, sample, key measurements, primary analysis
  • Results: ~40% — primary finding with quantitative anchor, ≤2 secondary findings
  • Conclusion: ~20% — take-home message; 1 forward-looking sentence (implication or next step)

For character-limited single-paragraph formats (e.g., SfN): Write as a single flowing paragraph in the order: context → objective → methods → results → conclusion. Compress methodological detail aggressively while keeping the key result and conclusion intact.

Step 3 — Compression Rules

When cutting to fit the word limit:

  1. Preserve: primary endpoint result (with N and statistics), study design, main conclusion
  2. Compress: methodological detail — give just enough to understand the design; cut specific reagent details, secondary analyses unless they are the main story
  3. Cut first: redundant background statements, hedging phrases ("It is well-known that..."), acknowledgment phrases, secondary results if over limit
  4. Never cut: the quantitative primary result; the take-home conclusion; sample size N
  5. Never fabricate: do not add results, effects, or conclusions not in the original

Step 4 — Count and Verify

After adapting, provide:

  1. The adapted abstract, fully formatted
  2. The word count (or character count) with a clear note: Word count: X / [limit]
    • For character-limited formats (e.g., SfN): state the count as [N] characters including spaces. SfN and most character-limited conferences count spaces. Users should verify using a tool that counts spaces (e.g., Python len() or Word character count with spaces enabled).
  3. A one-line note on any content that was cut to fit the limit, so the user can decide whether to restore it
  4. Word-limit conflict resolution: If preserving the primary result, sample size N, and conclusion still exceeds the word limit after aggressive cutting, notify the user: "Preserving required elements (primary result, N, conclusion) results in [X] words vs. [limit]. Please indicate which secondary elements to deprioritize." Do not silently cut required elements.

Step 5 — Final Check

  • Word/character count is within the specified limit
  • All required section headings are present (if structured format)
  • Primary quantitative result is included and accurate
  • No fabricated statistics, sample sizes, or conclusions added
  • Conclusion includes a take-home message (not just "more research is needed")
  • Abbreviations defined at first use within the abstract

Hard Rules

  • Never fabricate results, statistics, or conclusions not in the source material
  • Never exceed the stated word or character limit
  • If the source material lacks a quantitative result, ask the user to provide one rather than writing a vague conclusion
  • Always state the word count in the output

Abbreviation Rule

In conference abstracts, define every abbreviation at first use, even if it was defined in the full paper. Do not use ≥3 abbreviations in a 250-word abstract — spell out all but the most standard ones (e.g., RCT, CI, HR, OR are typically acceptable without definition).

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

Transform lengthy academic papers into concise, structured 250-word abstracts.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

Refines long medical academic texts into SCI-style unstructured Chinese and English abstracts; use when you need to condense drafts/reports/summaries into bilingual abstracts and generate Summary_Report.md.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

Analyze data with `adme-property-predictor` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

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。

aipoch/medical-research-skills1,9482026年9月17日 更新

aipoch のスキルをすべて見る

このスキルの問題を報告する