Agent skill

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.

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill policyengine-district-analysis-skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: none
Path: skills/analysis/policyengine-district-analysis-skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Congressional District Policy Analysis ## Documentation References - **Microsimulation API**: https://policyengine.github.io/policyengine-us/usage/microsimulation.html - **Parameter Discovery**: https://policyengine.github.io/policyengine-us/usage/parameter-discovery.html ## CRITICAL: Use calc() - No Manual Weights Ever **MicroSeries handles all weighting automatically. Never access .weights or do manual math.** ```python # ✅ CORRECT change = reformed.calc('household_net_income', period=2026, map_to='person') - \ baseline.calc('household_net_income', period=2026, map_to='person') loser_share = (change < 0).mean() # Weighted automatically! # ❌ WRONG loser_share = change.weights[change.values < 0].sum() / change.weights.sum() ``` ## Complete Example ```python from policyengine_us import Microsimulation from policyengine_core.reforms import Reform # 1. Load district data district = "NY-17" # Mike Lawler's district baseline = Microsimulation(dataset=f'hf://policyengine/policyengine-us-data/districts/{district}.h5') # 2. Define reform (find params with: grep -r "salt" policyengine_us/parameters/gov/irs/) reform = Reform.from_dict({ 'gov.irs.deductions.itemized.salt_and_real_estate.cap

What's inside
Steps it walks through
  1. Documentation References
  2. CRITICAL: Use calc() - No Manual Weights Ever
  3. Complete Example
  4. Compare to National
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the policyengine-district-analysis skill do?

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.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill policyengine-district-analysis-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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