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。
Adapt scientific abstracts to conference-specific word limits, section rules, and formatting constraints; use when reshaping an existing abstract for submission.
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。
Conference-specific abstract formatting.
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --help
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--abstract, -a | string | - | Yes | Abstract text file path |
--conference, -c | string | - | Yes | Target conference (ASGCT, ASCO, SfN, AACR, ASM) |
--output, -o | string | - | No | Output file path |
--list-conferences, -l | flag | - | No | List supported conferences |
# Adapt abstract for ASCO
python scripts/main.py --abstract my_abstract.txt --conference ASCO
# Save adapted abstract to file
python scripts/main.py --abstract my_abstract.txt --conference ASGCT --output adapted.txt
# List all supported conferences
python scripts/main.py --list-conferences
| Conference | Word Limit | Format |
|---|---|---|
| ASGCT | 250 words | Structured (Background/Methods/Results/Conclusion) |
| ASCO | 260 words | Structured (Background/Methods/Results/Conclusion) |
| SfN | 2000 chars | Single abstract |
| AACR | 300 words | Structured (Background/Methods/Results/Conclusion) |
| ASM | 300 words | Single abstract |
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
No additional Python packages required.
Every final response should make these items explicit when they are relevant:
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.This skill accepts requests that match the documented purpose of conference-abstract-adaptor 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:
conference-abstract-adaptoronly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Use the following fixed structure for non-trivial requests:
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
| Field | Required | Format/Source | Example | If Missing |
|---|---|---|---|---|
| User task description | Yes | Text | Research question, writing goal, analysis objective | Stop and ask user to provide |
| Primary input material | Depends on task | Text, file path, ID, table, or literature | PMID, PDF, CSV, DOCX, keywords, etc. | Specify which material type is missing |
| Output preference | No | Text | Language, format, target journal, template | Use skill default format |
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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。
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。
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。
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。
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。
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。