A framework for evidence-based city policy analysis. Built on world-class methodologies from the Bloomberg Centers at JHU & HKS, J-PAL at MIT, and The GovLab at NYU & Northeastern — connecting Claude AI to live open data from Boston, San Francisco, Seattle, and Washington DC.
Each skill guides Claude through a rigorous phase of city policy work, connecting directly to open data APIs via Model Context Protocol servers.
Stop solving the wrong problem. Scope challenges before touching data, map stakeholders, interrogate assumptions, and write a human-centered problem statement with explicit equity dimensions.
Five levels of evidence — descriptive, diagnostic, equity, counterfactual, synthesis — with explicit claim-strength labeling so analysts never overstate what administrative data can prove.
Translate analysis into audience-appropriate deliverables: executive memos, policy briefs, community fact sheets, dashboards — each with inclusive design and genuine engagement mechanics.
Is Boston's problem a Boston problem, or every city's problem? Uses San Francisco, Seattle, and DC open data MCPs for rigorous cross-city comparison — including performance management efficiency ratios — with J-PAL-calibrated claim language.
Connect what the city spends and who it employs to what it actually delivers. Cost per outcome, workload per FTE, and overtime signals from budget, payroll, and operational data — 311, permits, violations, and public safety.
Skills connect to open government data via Model Context Protocol servers — no manual downloads or API keys. Data flows directly into analysis on demand.
Primary analysis city. Full dataset coverage: 311 service requests, building permits, public safety, demographics, housing, transportation, environment.
Boston Open Data MCPPeer city for benchmarking. Comparable population (~870K), dense urban, strong Socrata data infrastructure. Covers 311, permits, public safety, budget, and payroll for performance comparisons.
San Francisco Open Data · SocrataPeer city for benchmarking. Comparable population (~750K), tech-sector city, Socrata platform. FindIt FixIt service request data enables direct 311 comparison.
Seattle Open Data · SocrataPeer city for benchmarking. Closest population match (~690K), CitiStat tradition (Boston's model), high urban density. DC Open Data uses ArcGIS platform.
DC Open Data · ArcGISThe Boston Open Data MCP eval suite measures whether Claude retrieves accurate, complete, and structurally correct data across all domains — from schema validation to cross-dataset analytical queries.
Tests dataset discovery and schema retrieval. Can the MCP find the right datasets, return correct field names, and confirm structural integrity? No domain knowledge required — just that the plumbing works.
Tests accurate counts, rankings, and aggregations from individual datasets. Covers 311, crime, building permits, Blue Bikes, and population — all with ground-truth tolerances set against immutable historical records.
Tests chained operations: filter by category, aggregate by group, sort, and interpret. Requires the MCP to execute multiple tool calls correctly and return ranked results in the right order.
Tests cross-dataset joins: per-capita rates, year-over-year comparisons, and multi-domain synthesis. Requires the MCP to navigate multiple datasets, calculate derived metrics, and reach directionally correct conclusions.
Get all skill files and supporting materials from GitHub.
Add SKILL.md files to your Claude environment. The master orchestrator routes to sub-skills automatically.
Add Boston, San Francisco, Seattle, and DC open data MCP servers to enable live data access.