PolicyEngine Claude

Official Claude Code plugin for PolicyEngine - a comprehensive knowledge base for users, analysts, and contributors across the entire PolicyEngine ecosystem.

Overview

PolicyEngine Claude provides agents, slash commands, and skills for working with PolicyEngine's 40+ repository ecosystem:

🤖 21 Specialized Agents - Automated workflows for development
🎯 4 Slash Commands - Multi-agent orchestration and PR workflows
📚 24 Skills - Knowledge base for users, analysts, and contributors

Quick Start

Install everything (recommended for most users):

/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install complete@policyengine-claude

This gives you all 21 agents, 4 commands, and 24 skills for the entire PolicyEngine ecosystem.

Or install selectively by use case:

Three Audiences, Targeted Plugins

👥 For Users

Learn to use PolicyEngine web apps, understand calculations, and interpret results.

Install:

/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install essential@policyengine-claude

Includes:

policyengine-user-guide-skill - Using the platform
policyengine-us-skill - Understanding US programs
policyengine-writing-skill - Communication style

📊 For Analysts

Create policy analyses, build dashboards, and conduct research using PolicyEngine programmatically.

Install:

/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install analysis-tools@policyengine-claude

Includes:

policyengine-python-client-skill - Programmatic access
policyengine-analysis-skill - Analysis patterns
microdf-skill - Data analysis utilities
policyengine-us-skill - Simulation patterns
policyengine-writing-skill - Report writing

💻 For Contributors

Develop PolicyEngine software across country models, API, app, and data packages.

Install:

# For country model development
/plugin install country-models@policyengine-claude

# For API development
/plugin install api-development@policyengine-claude

# For app development
/plugin install app-development@policyengine-claude

# For data science
/plugin install data-science@policyengine-claude

Skills Overview (14 Total)

User-Facing Skills

1. policyengine-user-guide 🆕

Using policyengine.org web apps
Creating reforms through UI
Understanding household and population results
Interpreting metrics (Gini, poverty, etc.)

2. policyengine-python-client 🆕

Programmatic API access
Using policyengine.py package
Batch calculations
Rate limits and authentication

Core Platform Skills

3. policyengine-core 🆕

Simulation engine architecture
Variable and parameter systems
Vectorization requirements
Formula patterns
Multi-audience: explains what Core is (users), how it works (analysts), how to develop it (contributors)

4. policyengine-us ✅ Enhanced

US tax and benefit system
Situation creation patterns
Variable reference (400+ variables)
Using axes for parameter sweeps
Multi-audience: what's modeled (users), how to use (analysts), how to develop (contributors)

5. policyengine-api 🆕

Flask REST API patterns
Endpoint structure
Caching strategy (Redis)
Background jobs (RQ)
Multi-audience: what API does (users), how to call it (analysts), how to develop (contributors)

6. policyengine-app 🆕

React application patterns
Component structure
Routing and state management
Chart integration (Plotly)
Multi-audience: app features (users), URL structure (analysts), development patterns (contributors)

Analysis and Data Skills

7. policyengine-analysis ✅ Enhanced

Impact analysis patterns
Streamlit dashboards
Jupyter notebooks
Plotly visualizations with PolicyEngine branding
Multi-audience: how analysis works (users), analysis code patterns (analysts)

8. microdf 🆕

Weighted pandas DataFrames
Inequality metrics (Gini, top shares)
Poverty calculations
Survey microdata analysis
Multi-audience: what microdf does (users), how to use (analysts), how to develop (contributors)

Data Ecosystem Skills

9. microimpute 🆕

ML-based variable imputation
Multiple methods (linear, random forest, quantile forest, XGBoost)
Quantile loss benchmarking
Used in policyengine-us-data to fill missing survey variables

10. microcalibrate 🆕

Survey weight calibration to population targets
L0 regularization for dataset sparsification
Automatic hyperparameter tuning (Optuna)
Interactive dashboard at microcalibrate.vercel.app

11. l0 🆕

PyTorch L0 regularization for neural networks
Intelligent sampling and feature selection
Used by microcalibrate for household selection
Based on Louizos et al. (2017) paper

Design and Standards Skills

12. policyengine-design 🆕

PolicyEngine visual identity (colors, fonts, logos)
Chart branding (Plotly format_fig pattern)
Streamlit theme configuration
Color palette and usage guidelines (v1: #39C6C0, v2: #319795)
Multi-audience: recognizing brand (users), applying branding (analysts/contributors)

13. policyengine-standards ✅

Code formatting (Black, Prettier)
Git workflow
Changelog management
CI requirements
Common AI pitfalls

14. policyengine-writing ✅

Active voice, quantitative language
Sentence case for headings
Neutral, objective tone
Blog post and PR description patterns

Agents (21 Total)

Country Model Agents (16)

Workflow agents:

document-collector - Gather authoritative sources
issue-manager - Manage GitHub issues and PRs
parameter-architect - Design parameter structures
test-creator - Write tests from documentation
rules-engineer - Implement variables/parameters
pr-pusher - Format and push PRs

Validators:

implementation-validator - Quality, patterns, hard-coding checks
cross-program-validator - Cross-program consistency
performance-optimizer - Vectorization opportunities
program-reviewer - Regulatory compliance review (researches law first)

Quality and CI:

documentation-enricher - Enhance documentation
edge-case-generator - Comprehensive test cases
ci-fixer - Fix CI failures (runs tests locally)

Isolation:

isolation-setup - Git worktrees for isolated development
isolation-enforcement - Ensure test/implementation isolation

Other:

integration-agent - Advanced merge workflows

Other Agents (5)

Root-level:

branch-comparator - Compare branches for differences
legislation-statute-analyzer - Analyze legislative text
reference-validator - Validate parameter references

API/App:

api-reviewer - Review Flask/API code
app-reviewer - Review React/app code

Slash Commands (4 Total)

/create-pr [title] 🆕

Create PR as draft and wait for CI to pass
Actually polls CI status (doesn't give up!)
Marks ready when all checks pass
Solves the "I'll check back later" problem
Example: /create-pr or /create-pr "Add new feature"

/encode-policy <program-name>

Orchestrate complete multi-agent workflow
Implement new government programs
Example: /encode-policy Idaho LIHEAP

/review-pr [pr-number]

Comprehensive PR review (read-only)
4 validators: regulatory accuracy, reference quality, code patterns, test coverage
Priority-based output (Critical/Should/Suggestions)
Post findings to GitHub
Example: /review-pr 123

/fix-pr [pr-number]

Apply fixes from review
Push updates automatically
Example: /fix-pr 123

Available Plugins (7)

Plugin	Audience	Agents	Commands	Skills
essential	Users	0	0	4
country-models	Contributors	16	4	15
api-development	Contributors	1	3	7
app-development	Contributors	1	3	7
analysis-tools	Analysts	0	0	9
data-science	Analysts/Contributors	0	0	10
complete	All	21	4	24

Installation

Install Everything

/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install complete@policyengine-claude

Install for Specific Use Cases

# Add marketplace first
/plugin marketplace add PolicyEngine/policyengine-claude

# Then install what you need:
/plugin install essential@policyengine-claude         # For users
/plugin install analysis-tools@policyengine-claude    # For analysts
/plugin install country-models@policyengine-claude    # For country devs
/plugin install api-development@policyengine-claude   # For API devs
/plugin install app-development@policyengine-claude   # For app devs
/plugin install data-science@policyengine-claude      # For data work

For Contributors

In specific repos (auto-install):

Each PolicyEngine repo has .claude/settings.json that auto-installs the appropriate plugin:

{
  "plugins": {
    "marketplaces": ["PolicyEngine/policyengine-claude"],
    "auto_install": ["country-models@policyengine-claude"]
  }
}

Result: When you trust the repo, the plugin auto-installs!

Multi-Repo Architecture

The PolicyEngine Ecosystem

Layer 0: Foundation
├── L0 (PyTorch regularization for sparsification)

Layer 1: Core Engine
├── policyengine-core (simulation engine)

Layer 2: Country Models (depend on core)
├── policyengine-us (US federal + 50 states)
├── policyengine-uk (UK tax and benefits)
├── policyengine-canada (Canada federal + provincial)
├── policyengine-il (Israel)
└── policyengine-ng (Nigeria)

Layer 3: Data Utilities
├── microdf (weighted DataFrames for analysis)
├── microimpute (ML variable imputation)
└── microcalibrate (survey calibration, uses L0)

Layer 4: Enhanced Data (depend on country models + data utilities)
├── policyengine-us-data (enhanced CPS, uses microimpute + microcalibrate)
└── policyengine-uk-data (enhanced FRS)

Layer 5: Services
├── policyengine-api (v1 - production Flask API)
├── policyengine-api-v2 (v2 - monorepo with 3 microservices, in development)
└── policyengine.py (Python client)

Layer 6: Interfaces
├── policyengine-app (v1 - production React app)
└── policyengine-app-v2 (v2 - Next.js + Mantine, in development)

Layer 7: Applications
├── Analysis repos (crfb-tob-impacts, newsletters, dashboards)
└── Calculators (givecalc, salt-amt-calculator, ctc-calculator)

Version status:

✅ v1 APIs and apps are current production
🚧 v2 APIs and apps are in active development
Skills cover both where relevant, with migration notes

Skills Point to Repos

Skills use a pointer pattern - they provide stable principles and point to current implementation:

## For Contributors

**To see current implementation:**
```bash
cat policyengine_api/endpoints/economy.py

To find patterns:

grep -r "cache_key" policyengine_api/


**Benefits:**
- ✅ No version drift - skills point to code
- ✅ Branch-aware - reads from your checkout
- ✅ Single source of truth - code is documentation
- ✅ Cross-repo learning - can explore related repos

### Multi-Repo Workflows

**Example: API contributor understanding country models**
```bash
# Working in policyengine-api
cd policyengine-api

# Claude has policyengine-api-skill installed
# Need to understand variable structure

# Claude can add related repo
/add-dir ../policyengine-us

# Now Claude can read both repos
# Uses policyengine-us-skill to understand variables
# Uses policyengine-api-skill to create endpoint

Example: Analyst debugging data issues

# Working in analysis repo
cd crfb-tob-impacts

# Has analysis-tools plugin
# Includes: microdf-skill, policyengine-us-skill

# Can install additional skills on-demand
/plugin install policyengine-us-data-skill@policyengine-claude

# Now can understand data pipeline issues

Repository-Specific Auto-Install

Each repo type installs appropriate plugins:

Repository	Plugin	What It Includes
policyengine-us	country-models	16 agents, 4 commands, 15 skills
policyengine-uk	country-models	16 agents, 4 commands, 15 skills
policyengine-api	api-development	1 agent, 3 commands, 7 skills
policyengine-app	app-development	1 agent, 3 commands, 7 skills
crfb-tob-impacts	analysis-tools	8 skills
givecalc	analysis-tools	8 skills
microdf	data-science	9 skills

How Skills Serve Multiple Audiences

Each skill organized with sections:

# Skill Name

## For Users 👥
[What this is, why it matters]

## For Analysts 📊
[How to use it programmatically]

## For Contributors 💻
[How to develop it]
**Current implementation:**
```bash
cat path/to/current/code.py


**Example: policyengine-us-skill**

- **Users** learn what programs are modeled (EITC, CTC, SNAP, etc.)
- **Analysts** learn situation creation and variable reference
- **Contributors** learn where to find implementation (`policyengine_us/variables/`)

## Key Innovation: Documentation Pointers

Instead of duplicating code, skills **point to repos**:

**Traditional approach (version drift):**
```markdown
## API Endpoint Pattern

```python
# Hardcoded example from when skill was written
# Gets outdated as code evolves
@app.route("/us/calculate")
def calculate():
    # Old pattern from 6 months ago


**PolicyEngine approach (always current):**
```markdown
## API Endpoint Pattern

**Current implementation:**
```bash
cat policyengine_api/endpoints/economy.py

Pattern demonstrated:

Request validation
Cache checking
Computation
Error handling


**Benefits:**
- Always shows current code
- Works with feature branches
- Single source of truth
- No maintenance burden

## Use Cases

### Use Case 1: User Learning the Platform

User: "How do I calculate how much I'd save from donating to charity?"

Claude: [Has policyengine-user-guide-skill] "Go to policyengine.org/us/household, enter your income and donation amount. The calculator shows your tax savings..."

[Points to givecalc for more advanced calculator]


### Use Case 2: Analyst Creating Impact Study

User in crfb-tob-impacts: "Analyze CTC expansion proposal"

Claude: [Has analysis-tools plugin] [Uses policyengine-python-client-skill for API access] [Uses policyengine-analysis-skill for dashboard patterns] [Uses microdf-skill for inequality calculations] [Uses policyengine-writing-skill for blog post]

Creates: Analysis notebook + Streamlit dashboard + blog post draft


### Use Case 3: Contributor Implementing New Program

User in policyengine-us: "/encode-policy California EITC"

Claude: [Has country-models plugin] Phase 1: [Invokes @issue-manager] → Creates issue, branch, draft PR Phase 2: [Invokes @document-collector] → Gathers CA EITC regulations + Checkpoint 1 Phase 3A: [Invokes @parameter-architect] → Creates parameters + Checkpoint 2 Phase 3B: [Invokes @test-creator + @rules-engineer in parallel] → Tests + Variables Phase 3C: [Invokes @edge-case-generator] → Edge cases + Checkpoint 3 Phase 4: [Invokes @implementation-validator] → Organization check & fix Phase 5: [Invokes @ci-fixer] → Run tests locally, fix failures Phase 6: [Invokes @pr-pusher] → Format and push Phase 7: [Invokes @program-reviewer] → Final review + PR description

Creates: Issue + Tests + Implementation + PR with full documentation


### Use Case 4: Creating PR That Waits for CI

User in policyengine-us: "Create a PR for these changes and mark ready when CI passes"

Claude: [Has country-models plugin] [Sees in policyengine-standards-skill: "Use /create-pr command"]

/create-pr

[Command creates draft PR #456] [Polls CI every 15 seconds] [After 3 minutes: "CI: 3/3 checks passed"] [Marks PR ready]

Result: "✅ PR #456 is ready for review! All CI checks passed."


**Problem solved:** Claude doesn't say "I'll check back later" and give up. It actually waits!

### Use Case 5: Cross-Repo Debugging

User in policyengine-api: "Why is EITC calculation wrong?"

Claude: [Has api-development plugin] "Let me check the endpoint... and the variable implementation"

/add-dir ../policyengine-us

[Reads API endpoint code using policyengine-api-skill] [Reads EITC variable code using policyengine-us-skill] [Compares and identifies discrepancy]

"The API is passing the wrong year parameter to the simulation..."


## Installation by Use Case

### Get Everything (Recommended)

```bash
/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install complete@policyengine-claude

Includes: All 21 agents, 4 commands, 24 skills for the entire PolicyEngine ecosystem.

Selective Installation

First: Add marketplace (if not already added)

/plugin marketplace add PolicyEngine/policyengine-claude

Then choose what you need:

Use Case	Command
Use PolicyEngine web app	`/plugin install essential@policyengine-claude`
Policy analysis with Python	`/plugin install analysis-tools@policyengine-claude`
Country model development	`/plugin install country-models@policyengine-claude`
API development	`/plugin install api-development@policyengine-claude`
App development	`/plugin install app-development@policyengine-claude`
Data science work	`/plugin install data-science@policyengine-claude`

Skills Catalog

Skill	Users	Analysts	Contributors	Key Topics
policyengine-user-guide	✅	⚪	⚪	Web app usage, understanding results
policyengine-python-client	⚪	✅	⚪	API access, policyengine.py package
policyengine-core	✅	✅	✅	Simulation engine, architecture
policyengine-us	✅	✅	✅	US tax/benefit system, variables
policyengine-api	⚪	✅	✅	REST endpoints (v1), caching, services
policyengine-app	⚪	⚪	✅	React components (v1), routing, charts
policyengine-analysis	✅	✅	⚪	Impact studies, dashboards, notebooks
microdf	✅	✅	✅	Inequality, poverty, weighted stats
microimpute	⚪	✅	✅	ML imputation, quantile forest
microcalibrate	⚪	✅	✅	Survey calibration, L0 sparsity
l0	⚪	✅	✅	Regularization, sampling gates
policyengine-design	✅	✅	✅	Colors (v1/v2), fonts, logos, branding
policyengine-standards	⚪	⚪	✅	Code formatting, Git, CI
policyengine-writing	✅	✅	✅	Active voice, quantitative, neutral

Team Setup

Auto-Install in Repositories

Add to .claude/settings.json in each repo:

policyengine-us:

{
  "plugins": {
    "marketplaces": ["PolicyEngine/policyengine-claude"],
    "auto_install": ["country-models@policyengine-claude"]
  }
}

policyengine-api:

{
  "plugins": {
    "marketplaces": ["PolicyEngine/policyengine-claude"],
    "auto_install": ["api-development@policyengine-claude"]
  }
}

crfb-tob-impacts (analysis repo):

{
  "plugins": {
    "marketplaces": ["PolicyEngine/policyengine-claude"],
    "auto_install": ["analysis-tools@policyengine-claude"]
  }
}

Result: Team members trust repo → plugin auto-installs → everyone has same knowledge base!

Plugin Distribution Strategy

Essential (For Everyone)

Target: All PolicyEngine users
What: Basic platform knowledge
Skills: user-guide, policyengine-us, writing

Country Models (For Country Package Development)

Target: Contributors to policyengine-us, policyengine-uk, etc.
What: Multi-agent workflow + simulation knowledge
Agents: 16 specialized agents
Commands: /encode-policy, /review-pr, /fix-pr, /create-pr
Skills: All 15 technical pattern and documentation skills

API Development (For API Contributors)

Target: policyengine-api contributors
What: API patterns and review
Agents: api-reviewer
Skills: api, core, us, standards, writing

App Development (For App Contributors)

Target: policyengine-app contributors
What: React patterns and review
Agents: app-reviewer
Skills: app, api, us, standards, writing

Analysis Tools (For Policy Analysts)

Target: Analysis repos, researchers
What: Analysis patterns and tools
Skills: user-guide, python-client, us, analysis, microdf, writing

Data Science (For Data Package Contributors)

Target: Data package contributors
What: Data analysis utilities
Skills: microdf, us, standards, writing

Multi-Repo Best Practices

Working Across Repositories

Use /add-dir to work with multiple repos:

# Start in one repo
cd policyengine-us

# Add related repo
/add-dir ../policyengine-core

# Claude can now read files from both repos
# Skills point to files in both repos

Benefits:

Single Claude session across repos
Skills work across repo boundaries
Understand dependencies
Debug cross-repo issues

Hierarchical CLAUDE.md Files

You can have CLAUDE.md in parent directory:

/Users/you/PolicyEngine/
├── CLAUDE.md                    # Loaded when in any child repo
├── policyengine-us/
│   └── CLAUDE.md                # Also loaded when in this repo
├── policyengine-api/
│   └── CLAUDE.md                # Also loaded when in this repo
└── crfb-tob-impacts/
    └── CLAUDE.md                # Also loaded when in this repo

Claude loads:

Parent CLAUDE.md (if exists)
Current repo CLAUDE.md (if exists)
Plugin skills (based on auto_install)

Migrating from Submodules

Old Way (Deprecated)

git submodule add https://github.com/PolicyEngine/.claude.git .claude
git submodule update --init --recursive

Problems:

Git submodule complexity
Update synchronization
Symlink issues
Per-repo configuration

New Way (Plugin System)

# Just add settings.json
{
  "plugins": {
    "marketplaces": ["PolicyEngine/policyengine-claude"],
    "auto_install": ["country-models@policyengine-claude"]
  }
}

Benefits:

No Git complexity
Auto-install for team
Easy updates
Works globally

Migration PRs Filed

Contributing

Adding New Skills

Create skill directory:
```
mkdir skills/my-new-skill
```

Create SKILL.md with sections:

---
name: my-skill
description: Brief description
---

# Skill Name

## For Users 👥
[What it is]

## For Analysts 📊
[How to use it]

## For Contributors 💻
[How to develop it]
**Current implementation:**
```bash
cat path/to/code.py

Add to marketplace.json
Test with Claude Code
Submit PR with changelog_entry.yaml

Skill Guidelines

DO include:

✅ Multi-audience sections (users, analysts, contributors)
✅ Stable principles and patterns
✅ Pointers to current implementation (file paths)
✅ Commands to explore repos (cat, grep, tree, ls)
✅ Cross-references to related skills
✅ Real examples from PolicyEngine repos

DON'T include:

❌ Hardcoded file contents (point to files instead)
❌ Version-specific implementation details
❌ Duplicate information from other skills
❌ Unstable, rapidly-changing patterns

Testing Skills

# Install locally
/plugin marketplace add PolicyEngine/policyengine-claude
/plugin install my-plugin@policyengine-claude

# Ask Claude to use the skill
"Use the my-skill to help me with X"

# Verify Claude can find and use it

Version History

v3.3.0 - Continuous regulatory verification and command redesign

Added 3 regulatory checkpoints to encode-policy (after Phase 2, 3A, 3C)
Redesigned review-pr: 4 phases, 4 agents, priority-based output (Critical/Should/Suggestions)
Rewritten fix-pr: 5 phases, dependency-order fixing (params → vars → tests)
Redesigned reference-validator: 5-phase workflow, detailed reference rules
Renamed policyengine-implementation-patterns-skill → policyengine-variable-patterns-skill
New policyengine-code-organization-skill for folder structure and naming
Deleted naming-coordinator agent (converted to skill)
Removed hardcoded username from review-pr

v3.2.4 - Workflow improvements and program-reviewer

Renamed tanf-program-reviewer to program-reviewer (generalized for any program)
Added program-reviewer to /review-pr command (Step 6: Regulatory Review)
Restructured encode-policy phases (4A/4B split, local testing in Phase 6)
ci-fixer now runs tests locally instead of waiting for GitHub CI
Added code pattern enforcement (adds vs add(), reference formats, etc.)
Added "Legal Code is Source of Truth" principle

v3.1.x - Skill loading and error handling

Added skill loading instructions to all agents
Added error handling framework to encode-policy
State-specific program naming (TEA, OWF, CalWORKs)

v3.0.0 - Simplified workflow

Simplified encode-policy from 9 to 8 phases
All agents work on same branch (no git worktrees needed)
Keep PR as draft (user decides when ready)

v2.0.0 - Comprehensive multi-audience skills

Added 6 new skills (user-guide, python-client, core, api, app, microdf)
Enhanced existing skills with multi-audience sections
Added essential and data-science plugins
Introduced documentation pointer pattern

v1.0.0 - Initial release

18 agents for country model development
3 slash commands
4 skills (us, analysis, standards, writing)

Support

Issues: https://github.com/PolicyEngine/policyengine-claude/issues
Discussions: https://github.com/PolicyEngine/policyengine-claude/discussions
Email: [email protected]

Related Resources

PolicyEngine Main: https://github.com/PolicyEngine
Website: https://policyengine.org
Documentation: https://policyengine.org/us/docs
Claude Code Docs: https://docs.claude.com/en/docs/claude-code
Plugin Docs: https://docs.claude.com/en/docs/claude-code/plugins

License

MIT License - see LICENSE file for details.

PolicyEngine - Computing the impact of public policy for everyone

Note: This may be the first comprehensive multi-repo, multi-audience Claude Code plugin marketplace. If you're building a similar multi-repo system, feel free to use this as a reference!

Name		Name	Last commit message	Last commit date
Latest commit History 94 Commits
.claude-plugin		.claude-plugin
.github		.github
agents		agents
commands		commands
skills		skills
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
ECOSYSTEM.md		ECOSYSTEM.md
LICENSE		LICENSE
README.md		README.md
changelog_entry.yaml		changelog_entry.yaml

License

PolicyEngine/policyengine-claude

Folders and files

Latest commit

History

Repository files navigation

PolicyEngine Claude

Overview

Quick Start

Three Audiences, Targeted Plugins

👥 For Users

📊 For Analysts

💻 For Contributors

Skills Overview (14 Total)

User-Facing Skills

Core Platform Skills

Analysis and Data Skills

Data Ecosystem Skills

Design and Standards Skills

Agents (21 Total)

Country Model Agents (16)

Other Agents (5)

Slash Commands (4 Total)

Available Plugins (7)

Installation

Install Everything

Install for Specific Use Cases

For Contributors

Multi-Repo Architecture

The PolicyEngine Ecosystem

Skills Point to Repos

Repository-Specific Auto-Install

How Skills Serve Multiple Audiences

Selective Installation

Skills Catalog

Team Setup

Auto-Install in Repositories

Plugin Distribution Strategy

Essential (For Everyone)

Country Models (For Country Package Development)

API Development (For API Contributors)

App Development (For App Contributors)

Analysis Tools (For Policy Analysts)

Data Science (For Data Package Contributors)

Multi-Repo Best Practices

Working Across Repositories

Hierarchical CLAUDE.md Files

Migrating from Submodules

Old Way (Deprecated)

New Way (Plugin System)

Migration PRs Filed

Contributing

Adding New Skills

Skill Guidelines

Testing Skills

Version History

Support

Related Resources

License

About

Resources

License

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Contributors 8

Uh oh!

Languages

Packages