Borrowing it
Nothing to install: this file belongs to Hack23/European-Parliament-MCP-Server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Hack23/European-Parliament-MCP-Server/main/.github/skills/political-science-analysis/SKILL.mdgit clone --depth 1 https://github.com/Hack23/European-Parliament-MCP-ServerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hack23/european-parliament-mcp-server/political-science-analysis)<a href="https://agentmods.dev/skills/hack23/european-parliament-mcp-server/political-science-analysis"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/political-science-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hack23/european-parliament-mcp-server/political-science-analysis"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/political-science-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.01098 |
| Opus 5 | $0.00010 | $0.00549 |
| Sonnet 5 | $0.00004 | $0.00220 |
| Haiku 4.5 | $0.00002 | $0.00110 |
Grade A, and why
political-science-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Political Science Analysis Skill
Context
This skill applies when:
- Analyzing MEP voting behavior patterns across 27 EU member states
- Studying political group cohesion and fragmentation in the European Parliament
- Evaluating EU legislative process dynamics (ordinary legislative procedure, consent, consultation)
- Performing comparative analysis of national delegation voting within transnational political groups
- Assessing policy positions using roll-call vote data from EP plenary sessions
- Studying coalition-building patterns between political groups (EPP, S&D, Renew, Greens/EFA, ECR, ID, The Left, NI)
- Analyzing rapporteur assignment patterns and committee influence
- Tracking political group switching and MEP mobility
This skill is grounded in the European Parliament MCP Server's access to EP Open Data Portal datasets and aligns with Hack23 ISMS Secure Development Policy for data integrity.
Rules
- Use Established Frameworks: Apply recognized political science methodologies — Hix-Noury-Roland spatial models, NOMINATE-style scaling for EP, Cohesion Index (Agreement Index) for political groups
- Distinguish Data Levels: Separate individual MEP votes, national delegation patterns, and political group aggregates — never conflate levels of analysis
- Account for Institutional Context: Consider EP's unique features: multilingual deliberation, rotating presidency influence, co-decision with Council, and committee gatekeeping power
- Control for Confounders: When analyzing voting behavior, control for national party discipline, political group whip strength, salience of policy area, and legislative procedure type
- Temporal Awareness: Respect legislative term boundaries (EP5–EP10), mid-term political group realignments, and enlargement effects (EU-15 → EU-27)
- Use EP-Specific Terminology: Reference rapporteurs (not sponsors), political groups (not parties), plenary (not floor), trilogue (not conference committee)
- Validate Against Multiple Sources: Cross-reference MCP Server data with VoteWatch Europe, EP Think Tank publications, and official EP roll-call records
- GDPR Compliance: MEP voting records are public data under EU transparency rules, but personal contact data requires GDPR-compliant handling per Hack23 Privacy Policy
- Attribution: Always cite European Parliament Open Data Portal as the authoritative data source
- Quantitative Rigor: Report confidence intervals, effect sizes, and sample sizes when presenting statistical findings on voting patterns
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 75 lines · 21 tokens per session scan A 608b95e2f934
political-science-analysis is a skill published in the GitHub repository Hack23/European-Parliament-MCP-Server (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 21 tokens to every session and 1,098 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
ue-mcp-epic-routing
Use when deciding between ue-mcp's native category actions and Epic's wrapped ToolsetRegistry tools (the epic actions, incl. the Blueprint graph DSL) for a task in Unreal. Pulls in when authoring Blueprint graph bodies, or any time both a native action and an epic action could do the job and you need to pick.
frontmcp-setup
Use when starting, scaffolding, or organizing a FrontMCP project. Covers creating a new project (CLI scaffold or manual) for Node, Vercel, and other targets; standalone versus Nx-monorepo layout, naming conventions, generators, and dependency rules; composing multiple @App classes, ESM packages, and remote MCP servers…
authoring-decorators
Use when the user wants to write a new prompt decorator - either a personal one for their repo or a contribution back to the upstream catalogue. Walks through the JSON schema, the extensions/ convention, how to verify a new decorator end-to-end through the hook, and how to diagnose failures using debug logging and…
apitap
ApiTap gives AI agents cheap access to web data through three layers.
you-finance
Answer finance questions through the You.com you-finance MCP tool, with payment-aware fallbacks for keyless hosts.