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/behavioral-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/behavioral-analysis)<a href="https://agentmods.dev/skills/hack23/european-parliament-mcp-server/behavioral-analysis"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/behavioral-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/behavioral-analysis"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/behavioral-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 | $0.00022 | $0.01311 |
| Opus 5 | $0.00011 | $0.00656 |
| Sonnet 5 | $0.00004 | $0.00262 |
| Haiku 4.5 | $0.00002 | $0.00131 |
Grade A, and why
behavioral-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 11d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Analysis Skill
Context
This skill applies when:
- Analyzing MEP voting psychology and decision-making patterns under uncertainty
- Studying political group dynamics including conformity, groupthink, and dissent within EP political groups
- Identifying cognitive biases in legislative decision-making (anchoring on Commission proposals, status quo bias)
- Evaluating MEP leadership styles and their influence on committee and political group effectiveness
- Assessing rapporteur and shadow rapporteur negotiation behavior in trilogue contexts
- Understanding MEP career incentives: re-election motivation, national party loyalty vs. EP group cohesion
- Detecting strategic behavior: log-rolling, vote-trading, and strategic abstention in plenary
- Profiling MEP activity patterns using participation data (votes, questions, speeches, reports)
This skill integrates behavioral science with EP MCP Server data, aligned with Hack23 ISMS data quality and privacy requirements.
Rules
- Behavioral Evidence Base: Ground psychological analysis in observable MEP behavior from MCP Server data — voting records, question frequency, report authorship, speech participation — not speculation about internal states
- Cognitive Bias Framework: Apply established cognitive bias taxonomy (Kahneman & Tversky) to EP decision-making — anchoring (Commission proposal as reference point), availability heuristic (salient recent events), and framing effects (how policy options are presented)
- Group Dynamics Theory: Use social psychology frameworks — Janis groupthink model, Tajfel social identity theory — to analyze political group cohesion and intergroup conflict in EP
- Principal-Agent Distinction: Recognize MEPs as agents with multiple principals — EP political group, national party, constituency, and personal conviction — analyze which principal dominates under different conditions
- Leadership Typology: Classify MEP leadership patterns using observable metrics — legislative output (reports), coalition-building (multi-group amendments), agenda-setting (questions, motions), and committee influence (chair/coordinator roles)
- Longitudinal Analysis: Track behavioral changes over an MEP's career and across legislative terms — first-term vs. experienced MEP behavior differs systematically
- Cultural Context: Account for national political culture effects on MEP behavior — consensual vs. adversarial traditions, attitudes toward EU integration, and negotiation styles
- Ethical Boundaries: Analyze public behavioral patterns only — do not construct psychological profiles of individual MEPs beyond what is observable in public parliamentary data per Hack23 Privacy Policy
- Statistical Validation: Use appropriate statistical tests when claiming behavioral patterns — report significance levels and control for confounders
- Falsifiability: Formulate behavioral hypotheses that can be tested against MCP Server data — avoid unfalsifiable claims about MEP motivations
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.
- 11d ago First seen · 96 lines · 22 tokens per session scan A e662ec70cfe5
behavioral-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 22 tokens to every session and 1,311 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.
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