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legislative-monitoring
Voting pattern analysis, committee effectiveness, legislative procedure tracking for European Parliament oversight
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Voting pattern analysis, committee effectiveness, legislative procedure tracking for European Parliament oversight
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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| name | legislative-monitoring |
| description | Voting pattern analysis, committee effectiveness, legislative procedure tracking for European Parliament oversight |
| license | MIT |
This skill applies when:
This skill enables systematic legislative oversight using EP MCP Server data, aligned with Hack23 ISMS data integrity and audit requirements.
Track a legislative dossier end-to-end using MCP Server tools:
1. Identify dossier: track_legislation (procedure reference, e.g., 2021/0106(COD))
2. Retrieve Commission proposal: search_documents (COM document type)
3. Monitor committee stage:
- Identify lead committee and rapporteur: get_meps (committee filter)
- Track committee amendments and vote: get_voting_records
4. Track plenary first reading:
- Retrieve adopted amendments: get_voting_records (adopted texts)
- Analyze voting results: roll-call vote data
5. Monitor Council position: (external source, cross-reference)
6. Track trilogue outcomes: track_legislation (procedure status updates)
7. Final adoption: search_documents (final adopted text)
Output: Timeline, key decision points, voting outcomes per stage
Analyze voting patterns in ENVI committee on climate legislation:
Methodology:
1. Identify ENVI climate dossiers: track_legislation (committee + policy filter)
2. Retrieve committee vote results: get_voting_records (committee reports)
3. Calculate per-group voting patterns on ENVI climate dossiers:
- EPP support rate for ambitious climate targets
- S&D-Greens alignment frequency
- ECR/ID opposition consistency
4. Identify swing votes: which groups determine outcomes
5. Track pattern changes within EP10 term
Metrics:
- Group cohesion per committee vote (Agreement Index)
- Cross-group coalition frequency and composition
- Minority opinion frequency (Rule 55 dissent reports)
Measure legislative influence through amendment tracking:
Using MCP Server data:
1. Count amendments tabled by political group per dossier
2. Track committee-stage adoption rates by group
3. Track plenary-stage adoption rates by group
4. Calculate survival rate: committee adoption → plenary adoption
5. Compare with EP-wide averages and historical baselines
Expected patterns:
- Rapporteur's group: highest adoption rate (60-80% in committee)
- Grand coalition groups: higher adoption in plenary
- Opposition groups: <20% adoption rate, mainly on technical amendments
- Committee coordinators: above-average success on compromise amendments