political-science
Analyze political data, fact-check claims, and study policy impacts using evidence-based methods
Best use case
political-science is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze political data, fact-check claims, and study policy impacts using evidence-based methods
Teams using political-science should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/political-science/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How political-science Compares
| Feature / Agent | political-science | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze political data, fact-check claims, and study policy impacts using evidence-based methods
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Political Science Analysis ## Purpose Analyze political phenomena, fact-check political claims, and evaluate policy impacts using rigorous methods. ## Key Datasets - **PolitiFact** (Jinyan1/PolitiFact): 6-level truth ratings for political statements - **VoteView** (voteview.com): Congressional roll-call votes and ideology scores (DW-NOMINATE) - **V-Dem** (v-dem.net): Varieties of Democracy — 400+ indicators for 202 countries since 1789 ## Analysis Types - **Fact-checking**: Verify political claims against authoritative data sources - **Policy analysis**: Evaluate policy impacts using causal inference methods - **Electoral analysis**: Voting patterns, swing analysis, demographic modeling - **Ideological mapping**: DW-NOMINATE scores, political spectrum positioning - **Comparative politics**: Cross-national institutional comparisons ## Protocol 1. **Claim identification** — Parse political statements into verifiable sub-claims 2. **Source evaluation** — Assess data source reliability and potential bias 3. **Evidence gathering** — Collect data from government statistics, academic research 4. **Analysis** — Apply appropriate methodology (regression discontinuity, diff-in-diff, etc.) 5. **Reporting** — Present findings with uncertainty, context, and caveats ## Rules - Maintain political neutrality — analyze evidence, not advocate positions - Distinguish between descriptive and normative claims - Report confidence intervals and uncertainty in predictions - Cite primary data sources (government statistics, peer-reviewed research) - Acknowledge when evidence is insufficient to draw conclusions
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