| name | meta-manuscript-generator |
| description | Generates a first draft of a clinical meta-analysis paper. Input the research report (including Methods and Results sections), language, and title to automatically generate a complete paper draft including Abstract, Introduction, Discussion, and other sections, with automatic ... |
| license | MIT |
| author | AIPOCH |
Source: https://github.com/aipoch/medical-research-skills
Meta-Analysis Manuscript Generator
Generates a first draft of a meta-analysis paper meeting SCI journal standards based on the user-provided research report, including reference support.
When to Use
- Use this skill when you need generates a first draft of a clinical meta-analysis paper. input the research report (including methods and results sections), language, and title to automatically generate a complete paper draft including abstract, introduction, discussion, and other sections, with automatic pubmed retrieval of relevant references. suitable for assisting in the writing of systematic reviews and meta-analyses in a reproducible workflow.
- Use this skill when a academic writing task needs a packaged method instead of ad-hoc freeform output.
- Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
- Use this skill when
scripts/insert_references.py is the most direct path to complete the request.
- Use this skill when you need the
meta-manuscript-generator package behavior rather than a generic answer.
Key Features
- Scope-focused workflow aligned to: Generates a first draft of a clinical meta-analysis paper. Input the research report (including Methods and Results sections), language, and title to automatically generate a complete paper draft including Abstract, Introduction, Discussion, and other sections, with automatic PubMed retrieval of relevant references. Suitable for assisting in the writing of systematic reviews and meta-analyses.
- Packaged executable path(s):
scripts/insert_references.py plus 1 additional script(s).
- Reference material available in
references/ for task-specific guidance.
- Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
Python: 3.10+. Repository baseline for current packaged skills.
Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.
Example Usage
cd "20260316/scientific-skills/Academic Writing/meta-manuscript-generator"
python -m py_compile scripts/insert_references.py
python scripts/insert_references.py --help
Example run plan:
- Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings.
- Run
python scripts/insert_references.py with the validated inputs.
- Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Workflow above for related details.
- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/insert_references.py with additional helper scripts under scripts/.
- Reference guidance:
references/ contains supporting rules, prompts, or checklists.
- Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Input Requirements
The user needs to provide:
- Research Report: Contains complete Methods and Results sections
- Methods and Results will be inserted directly into the final paper
- Should include detailed statistics (e.g., OR, HR, CI, p-values, etc.)
- Language: Chinese or English
- Title: Paper title
Input Format Example:
Methods and Results: (User's complete methods and results content...)
Language: (Chinese/English)
Title: (Paper title)
Workflow
Phase 1: Report Parsing
Extract and structure the following information from the research report:
Methods Section Keywords (for reference retrieval):
Study Population:
Exposure/Intervention:
Outcome Measures:
Research Direction:
Primary Research Methods:
Key Points of the Results Section(For discussion writing, extracted by module):
- Results Interpretation Module
Main findings and statistical data
Analysis of the relationship between exposure and outcomes
- Literature Comparison Module
Findings that need to be compared with previous studies
Contextual and background significance
- Clinical Implications Module
Results relevant to clinical significance
- Study Limitations Module
Methodological limitations
Stage 2: Reference Retrieval
Use scripts/search_references.py to retrieve PubMed references.
API Description:Use the official PubMed E-utilities API
- esearch: Retrieve PMID lists
- efetch: Retrieve detailed article information (XML format)
- Base URL:
https://eutils.ncbi.nlm.nih.gov/entrez/eutils
Search Workflow:
- Keyword Extraction:Extract 3–5 keywords from the topic and rank them by importance.
- Search Query Generation:Generate English search queries for each keyword.
- PubMed esearch Call:Retrieve a list of PMIDs that meet the criteria.
- PubMed efetch Call:Retrieve article details (authors, title, journal, year, abstract).
- Number of Articles Returned:
- First keyword: 15 articles
- Second keyword: 10 articles
- Other keywords: 5 articles each
- Limit to publications from the past 5 years (2020–2025)
Search Allocation:
- Introduction references: Search based on keywords from the Methods section
- Discussion – Results Interpretation: Search based on results interpretation points
- Discussion – Literature Comparison: Search based on literature comparison points
- Discussion – Study Limitations: Search based on keywords from the Methods section
Usage Example:
from scripts.search_references import search_references_for_theme
intro_refs = search_references_for_theme("immune checkpoint inhibitors non-small cell lung cancer efficacy meta-analysis")
discussion_refs = search_references_for_theme( "PD-1 inhibitors lung cancer survival mechanism")
Stage 3: Section Writing
Generate each section of the manuscript in the following order.
Detailed guidelines are available in references/writing-guide.md。
Citation Format During Writing:Use [PMID: xxxxxxxx] to mark references, which will be processed later
3.1 Abstract
- Four structured paragraphs: Background, Methods, Results, Conclusions
- 200-300 words
- No references required
3.2 Introduction
- Clinical background of the problem (with epidemiological data)
- Current research status and existing gaps
- Study objectives and significance
- 300–500 words
- No more than 10 references
3.3 Discussion
Write in modular order with natural transitions between sections:
| Module | Content | Word Count |
|---|
| Opening of Discussion | Summary of main findings and statistical significance | 150–200 |
| Results Interpretation | Mechanistic analysis and clinical relevance | ≥150 |
| Literature Comparison | Comparison with previous studies | ≥150 |
| Study Limitations | Methodological and clinical limitations | 100–150 |
| Closing of Discussion | Conclusions and future directions | 100–150 |
Each module should cite no more than 10 references.
Stage 4: Reference Insertion
Use scripts/insert_references.py to process references.
API Description:Use the PubMed efetch API to retrieve formatted citations
- Parse XML responses to generate AMA-style references
- Include: authors, title, journal abbreviation, year, volume, issue, pages
Processing Workflow:
-
Article Segmentation:Split the manuscript into sections using markers such as ## Discussion
-
PMID Extraction: Use regular expressions to identify [PMID: number] or 【PMID: number】
-
PubMed efetch Call:Retrieve full citation details for each PMID.
-
AMA Citation Generation:Format as:
Author(s). Title. Journal. Year;Volume(Issue):Pages.
-
In-text Citation Replacement:Replace [PMID: xxx] with [[n]](link) format
-
Renumbering Numeric Citations:Resolve conflicts with existing bracketed numeric citations.
-
Reference List Generation:Number references sequentially based on citation order.
Usage Example:
from scripts.insert_references import insert_references
final_article = insert_references(
article=draft_with_pmid_markers,
new_references=""
)
Stage 5: Final Integration and Output
Integrate the generated content with the user-provided Methods and Results sections into a complete manuscript.
Integration Order:
-
Title (user-provided)
-
Abstract (generated)
-
Introduction (generated)
-
Materials and Methods (extracted from user input, unchanged)
-
Results (extracted from user input, unchanged)
-
Discussion (generated)
-
Conclusion (generated)
-
References (generated)
Final Output Format:
# [Article Title]
## Abstract
[Abstract content]
## Introduction
[Introduction content with hyperlinks]
## Materials and Methods
[User-provided Methods section, original text preserved]
## Results
[User-provided Results section, original text preserved]
## Discussion
[Discussion content, no subheadings, natural flow]
## Conclusion
[Conclusion]
## Input Validation
This skill accepts requests that match the documented purpose of `meta-manuscript-generator` and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
> `meta-manuscript-generator` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
## References
[1] Author et al. Title. Journal. Year;Vol(Issue):Pages. [https://pubmed.ncbi.nlm.nih.gov/PMID/]
[2] ...
Note:The user-provided Methods and Results sections should be preserved in their original wording, with only minimal formatting adjustments made where necessary.
Writing Standards
- Language Style:Academic, objective, and precise
- Abbreviation Rules:Provide full term at first mention
- Citation Format:
- During drafting:
[PMID: 12345678]
- Final version:
[[1]](link)
- Data Presentation:Retain original statistical data, e.g.
HR = 1.25, 95% CI: 1.10–1.42, p < 0.001
- Avoid:Subjective judgments, overinterpretation, and redundant statements
Quality Checklist
Verify after generation:
Error Handling
- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If execution fails, report the failure point, summarize what can still be completed safely, and provide a manual fallback.
- Do not fabricate files, citations, data, search results, or execution outcomes.