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。
Generates FAQ lists from complex medical policies or protocols. Trigger when user provides medical documents, policies, or protocols and requests FAQ generation, patient education materials, or simplified explanations.
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。
Creates FAQ lists from medical documents.
See ## Features above for related details.
scripts/main.py.references/ for task-specific guidance.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.cd "20260318/scientific-skills/Academic Writing/faq-generator"
python -m py_compile scripts/main.py
python scripts/main.py --help
Example run plan:
CONFIG block or documented parameters if the script uses fixed settings.python scripts/main.py with the validated inputs.See ## Workflow above for related details.
scripts/main.py.references/ contains supporting rules, prompts, or checklists.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
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--input, -i | string | - | Yes | Source document file path |
--audience, -a | string | general | No | Target audience (patients, researchers, general) |
--output, -o | string | stdout | No | Output file path |
--format, -f | string | json | No | Output format (json, markdown, text) |
{
"faqs": [{"question": "", "answer": ""}],
"topic": "string"
}
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | No scripts included | Low |
| Network Access | No external API calls | Low |
| File System Access | Read-only within workspace | Low |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Input/output within session | Low |
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 faq-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:
faq-generatoronly 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.
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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。