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conference-abstract-adaptor

Adapt an existing scientific abstract to a conference's word or character limit and required structure. Receive reformatted text, a word count check, and a checklist of required sections for supported meetings such as ASCO, AACR, and SfN.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Adapt scientific abstracts to conference-specific word limits, section rules, and formatting constraints; use when reshaping an existing abstract for submission.

实测评分 未实测

查看安装方法

适用场景

  • Reshaping an abstract for a specific conference submission
  • Checking word or character limits before submission
  • Converting an abstract to a required section structure
  • Preparing versions for multiple conference submissions

包含的文件(5)

  • SKILL.md8.6 KB
  • eval_report_conference-abstract-adaptor_result.json10.7 KB
  • POLISH_CHANGELOG.md627 B
  • references/audit-reference.md640 B
  • scripts/main.py5.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

Conference Abstract Adaptor

Conference-specific abstract formatting.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

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

When to Use

  • Use this skill when the task needs Adapt abstracts to meet specific conference word limits and formats.
  • Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
  • Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Workflow

  1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
  2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
  3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
  4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
  5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Use Cases

  • Multi-conference submissions
  • Word count compliance
  • Format standardization
  • Deadline management

Parameters

ParameterTypeDefaultRequiredDescription
--abstract, -astring-YesAbstract text file path
--conference, -cstring-YesTarget conference (ASGCT, ASCO, SfN, AACR, ASM)
--output, -ostring-NoOutput file path
--list-conferences, -lflag-NoList supported conferences

Usage

# 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

Supported Conferences

ConferenceWord LimitFormat
ASGCT250 wordsStructured (Background/Methods/Results/Conclusion)
ASCO260 wordsStructured (Background/Methods/Results/Conclusion)
SfN2000 charsSingle abstract
AACR300 wordsStructured (Background/Methods/Results/Conclusion)
ASM300 wordsSingle abstract

Returns

  • Reformatted abstract
  • Word count verification
  • Required sections checklist
  • Submission-ready text

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable

Test Cases

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support

Output Requirements

Every final response should make these items explicit when they are relevant:

  • Objective or requested deliverable
  • Inputs used and assumptions introduced
  • Workflow or decision path
  • Core result, recommendation, or artifact
  • Constraints, risks, caveats, or validation needs
  • Unresolved items and next-step checks

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 scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
  • Do not fabricate files, citations, data, search results, or execution outcomes.

Input Validation

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-adaptor only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

Response Template

Use the following fixed structure for non-trivial requests:

  1. Objective
  2. Inputs Received
  3. Assumptions
  4. Workflow
  5. Deliverable
  6. Risks and Limits
  7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

When Not to Use

  • Do not proceed when required input files, identifiers, parameters, or context are missing — ask the user to provide them first.
  • Do not assume capabilities beyond this skill's declared scope when the user requests external operations or inferences.
  • Do not proceed without user confirmation when overwriting existing results, executing high-cost batch operations, or expanding task scope.

Required Inputs

FieldRequiredFormat/SourceExampleIf Missing
User task descriptionYesTextResearch question, writing goal, analysis objectiveStop and ask user to provide
Primary input materialDepends on taskText, file path, ID, table, or literaturePMID, PDF, CSV, DOCX, keywords, etc.Specify which material type is missing
Output preferenceNoTextLanguage, format, target journal, templateUse skill default format

Output Contract

  • Primary output: Structured result or target file aligned with this skill's objective.
  • Optional output: Intermediate check notes, issue list, supplementary suggestions, or generated file paths.
  • Format requirement: Unless the user specifies otherwise, prefer stable, reviewable Markdown or JSON; if the skill's bundled script requires a fixed format, use that format.
  • If partially complete: Must explicitly mark as PARTIAL and state which steps are completed and which remain.

Failure Handling

  • Missing critical input: Explicitly state which fields, files, or identifiers are missing and pause.
  • Script, template, or resource execution failure: Report the failing step, likely cause, and recovery suggestions — do not silently degrade.
  • Partial completion only: Return the verified portion first, then list remaining blockers and suggested next steps.

User Checkpoints

  • Before executing batch processing, overwriting files, long-running searches, or multi-stage generation, confirm scope and output format with the user.
  • Before proceeding when a key judgment is ambiguous, evidence is insufficient, or the workflow is entering the next stage, confirm with the user.

Quick Validation

  • Check that key scripts, templates, or reference file paths this skill depends on exist.
  • Check that the final output contains the core fields, sections, or files specified for this task.
  • Check that results clearly mark assumptions, limitations, and incomplete items.

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中文简介正在准备中。当前显示英语简介。

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