ReddRadar
Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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policyengine-modal-deployment
Deploying PolicyEngine backend APIs to Modal — workspace setup, authentication, deployment commands, environments, and troubleshooting
PolicyEngine/policyengine-claude 26
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policyengine-microsimulation
ALWAYS USE THIS SKILL for PolicyEngine microsimulation, population-level analysis, winners/losers calculations.
Triggers: "microsimulation", "share who would lose/gain", "policy impact", "national average", "weighted analysis",
"cost", "revenue impact", "budgetary", "estimate the cost", "federal revenues", "tax revenue", "budget score",
"how much would it cost", "how much would the policy cost", "total cost of", "aggregate impact",
"cost to the government", "revenue loss", "fiscal impact",
"poverty impact", "child poverty", "deep poverty", "poverty rate", "poverty reduction",
"how many people lifted out of poverty", "SPM poverty", "distributional impact",
"state tax", "state-level", "California", "New York",
"UBI", "universal basic income", "flat tax", "standard deduction",
"winners and losers", "winners", "losers",
"inequality", "Gini", "decile",
"SALT", "marginal tax rate", "effective tax rate".
NOT for single-household calculations like "what would my benefit be" — use policyengine-us or policyengine-uk for those.
Use this skill's code pattern, but explore the codebase to find specific parameter paths if needed.
PolicyEngine/policyengine-claude 26
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policyengine-analysis
Common analysis patterns for PolicyEngine research repositories (CRFB, newsletters, dashboards, impact studies).
For population-level estimates (cost, poverty, distributional impacts), use the policyengine-microsimulation skill instead.
PolicyEngine/policyengine-claude 26
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policyengine-district-analysis
Analyze policy impacts for congressional districts and representatives' constituents. Use when the user mentions a specific district (NY-17, CA-52), a representative's name, or asks about geographic policy impacts at district level. Provides HuggingFace district datasets.
PolicyEngine/policyengine-claude 26
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policyengine-recharts
Recharts chart patterns, formatting, and styling for PolicyEngine apps
PolicyEngine/policyengine-claude 26
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policyengine-vectorization
PolicyEngine vectorization patterns - NumPy operations, where/select usage, avoiding scalar logic with arrays
PolicyEngine/policyengine-claude 26
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python
ALWAYS LOAD THIS SKILL before setting up any Python environment or installing packages.
Defines the standard: uv, Python 3.13, uv pip install, .venv at project root.
Triggers: "set up python", "install python", "create a venv", "virtual environment",
"pip install", "install packages", "uv pip", "uv venv", "python version",
"VIRTUAL_ENV", "venv conflict", "which python", "activate", "deactivate",
"run the script", "run with uv", "uv run", "pyproject.toml", "install dependencies",
"install requirements", "install the package", "editable install", "pip install -e".
PolicyEngine/policyengine-claude 26
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policyengine-code-organization
Code organization patterns for PolicyEngine - variable naming conventions, folder structure, file organization
PolicyEngine/policyengine-claude 26
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policyengine-review-patterns
PolicyEngine code review patterns - validation checklist, common issues, review standards
PolicyEngine/policyengine-claude 26
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policyengine-period-patterns
PolicyEngine period handling - converting between YEAR, MONTH definition periods and testing patterns
PolicyEngine/policyengine-claude 26
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policyengine-code-style
PolicyEngine code writing style guide - formula optimization, direct returns, eliminating unnecessary variables
PolicyEngine/policyengine-claude 26
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policyengine-testing-patterns
PolicyEngine testing patterns - YAML test structure, naming conventions, period handling, and quality standards
PolicyEngine/policyengine-claude 26
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policyengine-data-testing
Testing patterns for PolicyEngine data generation pipelines (policyengine-us-data, policyengine-uk-data)
PolicyEngine/policyengine-claude 26
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policyengine-test-writing
This skill should be used when writing unit tests, integration tests, or test fixtures for
PolicyEngine frontend apps, APIs, SDKs, and standalone tools. NOT for country model packages
(policyengine-us, policyengine-uk, etc.) — those use YAML-based tests with their own conventions.
Covers the Given-When-Then naming convention, fixture extraction, edge case coverage, and the
rule that only modified test files should be run.
Triggers: "write tests", "add tests", "unit test", "test file", "test coverage", "write a test for",
"test this function", "test this component", "given when then", "test fixtures", "mock setup",
"edge cases", "test naming", "test convention"
PolicyEngine/policyengine-claude 26
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policyengine-parameter-patterns
PolicyEngine parameter patterns - YAML structure, naming conventions, metadata requirements, federal/state separation
PolicyEngine/policyengine-claude 26
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seo-checklist
SEO first principles for PolicyEngine web applications - meta tags, crawlability, performance, and dual-mode (standalone + iframe) considerations
PolicyEngine/policyengine-claude 26
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policyengine-reform-patterns
PolicyEngine reform patterns - factory functions, contrib parameters, in_effect toggles, registration, and test keys for contributed policy reforms
PolicyEngine/policyengine-claude 26
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policyengine-variable-patterns
PolicyEngine variable patterns - variable creation, no hard-coding principle, federal/state separation, metadata standards
PolicyEngine/policyengine-claude 26
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policyengine-aggregation
PolicyEngine aggregation patterns - using adds attribute and add() function for summing variables across entities
PolicyEngine/policyengine-claude 26
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microimpute
ML-based variable imputation for survey data - used in policyengine-us-data to fill missing values.
Triggers: "impute", "imputation", "missing values", "donor", "recipient", "quantile forest", "statistical matching", "PUF", "microimpute", "fill missing"
PolicyEngine/policyengine-claude 26
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microcalibrate
Survey weight calibration to match population targets - used in policyengine-us-data for enhanced microdata.
Triggers: "calibrate", "calibration", "survey weights", "reweighting", "population targets", "benchmarks", "microcalibrate", "weight adjustment", "target matching"
PolicyEngine/policyengine-claude 26
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l0
L0 regularization for neural network sparsification and intelligent sampling - used in survey calibration.
Triggers: "L0", "sparsification", "sample selection", "hard concrete", "sparse weights", "household selection", "gate", "survey sparsity", "l0-python"
PolicyEngine/policyengine-claude 26
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policyengine-uk-data
UK survey data enhancement - FRS with WAS imputation patterns and cross-repo variable workflows.
Triggers: "FRS", "Family Resources Survey", "WAS", "Wealth and Assets Survey", "UK data", "UK microdata", "wealth imputation", "policyengine-uk-data"
PolicyEngine/policyengine-claude 26
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microdf
Weighted pandas DataFrames for survey microdata analysis - inequality, poverty, and distributional calculations.
Triggers: "weighted mean", "Gini", "poverty rate", "inequality", "MicroDataFrame", "MicroSeries", "weighted statistics", "decile", "quintile", "income distribution", "microdf"
PolicyEngine/policyengine-claude 26