academic-highlight-generator
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.
Best use case
academic-highlight-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using academic-highlight-generator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/academic-highlight-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How academic-highlight-generator Compares
| Feature / Agent | academic-highlight-generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) # Academic Highlight Generator Generate journal-ready `Highlights` that can be pasted directly into a submission system. This skill is for **academic writing output**, not for inventing missing results. ## When to Use - The user wants a `Highlights` section for a manuscript submission. - The source is an English manuscript, abstract, results summary, or extracted full text. - The paper falls into one of these types: Original Research, Meta-analysis, Review, Case Report, Bioinformatics, Bibliometrics, or Technical Note. - The user needs a deterministic, concise output with strict bullet-count and length limits. ## When Not to Use - The user asks you to fabricate results, novelty claims, study counts, effect sizes, or conclusions that are not in the source. - The source text is too short to identify study type or key findings reliably. - The document is a perspective, commentary, editorial, or otherwise unsuitable for formal submission highlights. - The user provides a binary `.doc` file. This package supports `.txt`, `.pdf`, and `.docx`; convert `.doc` before continuing. ## Required Inputs Provide one of the following: - Plain manuscript text, abstract, or structured study summary. - A supported source file path for `scripts/extract_text.py`: `.txt`, `.pdf`, or `.docx`. Recommended metadata if available: - Manuscript type or target journal. - Core method, main findings, and significance sentence. - Any wording constraints such as British/American spelling. ## Output Contract Always return: ```text Highlights - <bullet 1> - <bullet 2> - <bullet 3> [- <bullet 4>] [- <bullet 5>] ``` Hard requirements: - Exactly `3-5` bullets. - English bullets only unless the user explicitly requests Chinese. - Maximum `85` characters per English bullet. - Objective third-person tone. - No first person (`we`, `our`). - No undefined abbreviations, citation markers, or figure/table references. - Every bullet must be grounded in source material. ## Supported Execution Paths ### Path A: Source text already provided Use the provided text directly. This is the preferred path for speed and determinism. ### Path B: Source file needs extraction Use: ```bash python scripts/extract_text.py <file_path> ``` Supported formats: - `.txt` - `.pdf` - `.docx` Unsupported format: - `.doc` -> ask the user to convert to `.docx` or `.pdf` first. ## Workflow ### 1. Validate source sufficiency Before writing anything, confirm the source contains enough signal to identify: - study type - method or evidence base - main finding or conclusion If not, stop and use the refusal template in `## Fallback and Refusal Contract`. ### 2. Extract text if needed If the user provided a file instead of text, run: ```bash python scripts/extract_text.py <file_path> ``` If extraction fails: - report the exact failure, - preserve the original file path in the message, - do not invent content from the missing file. ### 3. Detect article type Use `references/prompts.md` to classify the manuscript into one of: - Original Research - Meta-analysis - Review - Case Report / Case Series - Bioinformatics Study - Perspective / Commentary - Education / Policy Research - Bibliometric Analysis - Short Communication / Technical Note - Other / Unclear ### 4. Generate draft highlights Select the matching generation prompt from `references/prompts.md`. Coverage priorities by type: - Original Research: method, main result, mechanism/utility, significance - Meta-analysis / Review: evidence base, synthesis method, conclusion, gap/future direction - Case Report: case feature, diagnostic or treatment learning point, follow-up significance - Bioinformatics: data source, analytic method, marker/pathway/model, biological relevance - Bibliometrics: database, time span, tools, hotspots/trends, collaboration pattern - Technical Note: method/device/process optimization, efficiency or usability gain ### 5. Self-critique and refine Use the critique and refinement prompts in `references/prompts.md`. The final output must satisfy all of these checks: - `3-5` bullets - no bullet exceeds the limit - the bullets are not copied verbatim from the abstract - the set covers method + finding + value at least once - no fabricated numbers or study claims ## Fallback and Refusal Contract If the source is unsuitable or insufficient, respond with this structure: ```text Cannot generate submission-ready Highlights yet. Reason: <insufficient source / unsupported article type / unsupported file format> Detected type: <type or Unknown> Minimum additional input needed: - <item 1> - <item 2> ``` Use this refusal contract when: - the article type is `Other / Unclear`, - the text is too short to ground claims, - the user asks for invention rather than extraction, - the file format is unsupported. ## Deterministic Rules - Keep the same output header every time: `Highlights`. - Do not switch between sentence fragments and full sentences in one output. - Prefer one factual claim per bullet. - If a key value is unavailable, omit that value instead of guessing it. - If the source supports only three safe bullets, output three rather than padding to five. ## Quality Checklist Before returning the final answer, verify: - Study type and bullet focus are aligned. - No unsupported causal overstatement appears. - No clinical recommendation is implied unless the source itself states one cautiously. - Each bullet is independently readable. - The final output can be pasted into a journal submission form without reformatting.
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