conference-tweet-generator
$
npx mdskill add aipoch/medical-research-skills/conference-tweet-generatorTransforms conference abstracts into engaging social media content.
- Converts academic abstracts into tweets with summaries and titles.
- Requires Python 3.10 and third-party packages for execution.
- Executes structured workflows to ensure consistent output quality.
- Delivers formatted social media posts ready for publication.
SKILL.md
.github/skills/conference-tweet-generatorView on GitHub ↗
---
name: conference-tweet-generator
description: Generates academic conference tweets and summaries by filtering abstracts, translating content, and creating engaging titles. Use when you need to process conference abstracts into social media content.
license: MIT
author: aipoch
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
## When to Use
- Use this skill when the request matches its documented task boundary.
- Use it when the user can provide the required inputs and expects a structured deliverable.
- Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.
## Key Features
- Scope-focused workflow aligned to: Generates academic conference tweets and summaries by filtering abstracts, translating content, and creating engaging titles. Use when you need to process conference abstracts into social media content.
- Packaged executable path(s): `scripts/validate_skill.py`.
- 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
```bash
cd "20260316/scientific-skills/Others/conference-tweet-generator"
python -m py_compile scripts/validate_skill.py
python scripts/validate_skill.py --help
```
Example run plan:
1. Confirm the user input, output path, and any required config values.
2. Edit the in-file `CONFIG` block or documented parameters if the script uses fixed settings.
3. Run `python scripts/validate_skill.py` with the validated inputs.
4. 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/validate_skill.py`.
- 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.
## Validation Shortcut
Run this minimal command first to verify the supported execution path:
```bash
python scripts/validate_skill.py --help
```
# Conference Tweet Generator
This skill processes academic conference abstracts to generate engaging tweets and summaries.
## Workflow
1. **Search Meeting Info**: Use `tavily_search` to find background information about the conference (e.g., "ASCO 2025").
2. **Filter Abstracts**: Review the provided abstracts and filter those relevant to the specified topic.
3. **Process Abstracts**: For each selected abstract:
- Extract key content (Background, Methods, Results, Conclusion).
- **Translate Drug Names**: strictly use the dictionary in `references/drug_dictionary.md`.
- Format the output as a structured summary.
4. **Generate Titles**: Create 3 high-impact tweet titles following the format "Year Conference | Content".
5. **Generate Introduction**: Write a brief meeting introduction based on the search results.
## Requirements
- **Drug Translation**: You must refer to `references/drug_dictionary.md` for accurate drug name translations.
- **No Fabrication**: Do not invent meeting details; rely on search results.
## When Not to Use
- Do not use this skill when the required source data, identifiers, files, or credentials are missing.
- Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
- Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.
## Required Inputs
- A clearly specified task goal aligned with the documented scope.
- All required files, identifiers, parameters, or environment variables before execution.
- Any domain constraints, formatting requirements, and expected output destination if applicable.
## Output Contract
- Return a structured deliverable that is directly usable without reformatting.
- If a file is produced, prefer a deterministic output name such as `conference_tweet_generator_result.md` unless the skill documentation defines a better convention.
- Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.
## Validation and Safety Rules
- Validate required inputs before execution and stop early when mandatory fields or files are missing.
- Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
- Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
- Keep the output safe, reproducible, and within the documented scope at all times.
## Failure Handling
- If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
- If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
- If partial output is returned, label it clearly and identify which checks could not be completed.
## Quick Validation
Run this minimal verification path before full execution when possible:
```text
No local script validation step is required for this skill.
```
Expected output format:
```text
Result file: conference_tweet_generator_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any
```
## Deterministic Output Rules
- Use the same section order for every supported request of this skill.
- Keep output field names stable and do not rename documented keys across examples.
- If a value is unavailable, emit an explicit placeholder instead of omitting the field.
## Completion Checklist
- Confirm all required inputs were present and valid.
- Confirm the supported execution path completed without unresolved errors.
- Confirm the final deliverable matches the documented format exactly.
- Confirm assumptions, limitations, and warnings are surfaced explicitly.
More from aipoch/medical-research-skills
- 3d-molecule-ray-tracerGenerate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.
- abstract-summarizerTransform lengthy academic papers into concise, structured 250-word abstracts.
- abstract-trimmerPrecision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.
- academic-abstract-refinerRefines 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.
- academic-cv-generatorGenerate structured academic CVs from free-form Chinese/English text and export to Word (.docx). Use this skill when you are asked to organize, generate, or optimize an academic CV (e.g., publications/projects/awards) into a consistent, formatted document with uniform-colored section headers and optional bilingual output.
- academic-highlight-generatorGenerates 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.
- academic-norm-reviewDetects content similarity, verifies standardized citations and abbreviations, and flags potential academic integrity risks; use it before submission, during academic writing QA, or for compliance reviews.
- academic-poster-generatorComplete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster (beamerposter/tikzposter/baposter) with mandatory figure generation and a final rendered HTML deliverable.
- acronym-unpackerIntelligent medical abbreviation disambiguation tool that resolves ambiguous acronyms using clinical context, specialty-specific knowledge, and document-level semantic analysis.
- active-comparator-single-soc-faers-safety-comparisonGenerates 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.