wprdc

Name: wprdc
Author: diegosouzapw

AI Verified v1.1.0

Repo stars 39
Author updated Live
Author repo awesome-omni-skill

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: AI
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 92 / 100 · audit passed
Author / version / license: @diegosouzapw · v1.1.0 · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: No special requirements
Permissions: Read-only
Write / modify
Shell exec
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview wprdc.preview

---
name: wprdc
description: Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property ass…
category: ai
runtime: no special runtime
---

# wprdc output preview

## PART A: Task fit
- Use case: Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property assessments, air quality, 311 requests, jail census, overdose data, permits, violations, and more. Run SQL queries against live tables without downloading. Use when user asks about Pittsburgh/Allegheny County public data, property lookups, civic data, or regional statistics..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Quick Start / Commands / search <query>” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property assessments, air quality, 311 requests, jail census, overdose data, permits, violations, and more. Run SQL queries against live tables without downloading. Use when user asks about Pittsburgh/Allegheny County public data, property lookups, civic data, or regional statistics.”.
- **02** When the source has headings, the agent prioritizes “Quick Start / Commands / search <query>” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: wprdc
description: Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property ass…
category: ai
source: diegosouzapw/awesome-omni-skill
---

# wprdc

## When to use
- Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property assessments, air quality…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “Quick Start / Commands / search <query>” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "wprdc" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Quick Start / Commands / search <query>
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Query Pittsburgh's Western PA Regional Data Center (WPRDC) — 363+ datasets covering property assessments, air quality, 311 reque…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Quick Start”, “Commands”, “search ”, “info ”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name wprdc directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Quick Start / Commands / search ” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write / shell-exec; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

WPRDC - Pittsburgh Regional Data Center

Query 363+ datasets from the Western PA Regional Data Center. Property assessments, air quality, 311 requests, jail census, overdose data, parking, permits, violations — all queryable via SQL without downloading.

Quick Start

# Search for datasets
<skill>/wprdc.py search "property sales"
<skill>/wprdc.py search "air quality" --org allegheny-county

# Get dataset info
<skill>/wprdc.py info property-assessments

# List resources (tables) in a dataset
<skill>/wprdc.py resources property-assessments

# See field schema
<skill>/wprdc.py fields assessments

# SQL query (the killer feature!)
<skill>/wprdc.py query 'SELECT "PARID", "PROPERTYADDRESS" FROM @assessments WHERE "PROPERTYCITY"='"'"'PITTSBURGH'"'"' LIMIT 5'

# Quick parcel lookup
<skill>/wprdc.py parcel 0028F00194000000

# Download a dataset
<skill>/wprdc.py download property-assessments --format csv

Commands

`search <query>`

Search for datasets by keyword.

Options:

--org <name> — Filter by organization (e.g., allegheny-county, city-of-pittsburgh)
--group <name> — Filter by topic group (e.g., health, housing-properties)
--limit <n> — Max results (default: 10)
--json — Raw JSON output

`info <dataset>`

Get detailed information about a dataset, including description, resources, and metadata.

`resources <dataset>`

List all resources (tables/files) in a dataset with their IDs and queryability status.

`fields <resource>`

Show the field schema for a resource. Use shortcut names or resource IDs.

`query <sql>`

Execute SQL queries against live data. This is the power feature!

Important: Column names must be double-quoted because PostgreSQL is case-sensitive:

SELECT "PARID", "PROPERTYADDRESS" FROM @assessments WHERE "PROPERTYCITY"='PITTSBURGH' LIMIT 5

Use @shortcut notation for common tables (see Shortcuts below).

Options:

--json — Raw JSON output
--table — Format as ASCII table

`parcel <pin>`

Quick property lookup by parcel ID. Returns address, assessments, building info, and last sale.

<skill>/wprdc.py parcel 0028F00194000000

`download <dataset>`

Download a resource to a file.

Options:

--resource <id|name> — Specific resource
--format <csv|json|geojson> — Preferred format
--output <path> — Output filename

`orgs`

List all organizations publishing data.

`groups`

List all topic groups (categories).

`shortcuts`

Show available query shortcuts.

Query Shortcuts

Use @shortcut in SQL queries instead of long resource IDs:

Shortcut	Dataset
`@assessments`	Property Assessments (584K parcels)
`@sales`	Property Sales
`@311`	311 Service Requests
`@permits`	PLI Permits
`@violations`	PLI Violations
`@overdoses`	Fatal Accidental Overdoses
`@jail`	Jail Daily Census
`@air-quality`	Air Quality
`@fishfry`	Fish Fry Map

Example:

<skill>/wprdc.py query 'SELECT * FROM @overdoses WHERE "death_year"=2024 LIMIT 10'

Before Querying, Ask Yourself

Scope: Is this City of Pittsburgh only, or all of Allegheny County?
- PLI violations, 311, permits → City of Pittsburgh only (90 neighborhoods)
- Property assessments, overdoses, jail → All of Allegheny County (130 municipalities)
Freshness: When was this dataset last updated? Run info <dataset> first.
Fields: What columns exist? Run fields <resource> before writing SQL.
Size: How many records? Start with LIMIT 10, expand once you know it works.

NEVER Do

NEVER use CAST(), ROUND(), AVG(), or other SQL functions — WPRDC blocks them. You'll get "Access denied: Not authorized to call function". Do aggregation client-side.
NEVER query without LIMIT on large tables — Assessments has 584K rows. Queries timeout. Always add LIMIT.
NEVER assume county-wide coverage for City datasets — PLI violations, 311, permits are City of Pittsburgh only. Aspinwall, Fox Chapel, Mt. Lebanon = separate municipalities, not in the data.
NEVER trust "under maintenance" datasets — County plumbing inspections, housing inspections, food facilities are currently broken. Check info first.
NEVER forget column quoting — UPPERCASE columns need double quotes ("PARID"), lowercase don't (case_year). Wrong quoting = cryptic "column does not exist" errors.
NEVER use wildcards on unindexed text — LIKE '%something%' on large tables will timeout. Be specific.

Common Errors

Error	Cause	Fix
`409 CONFLICT` + "column does not exist"	Unquoted uppercase column	Add quotes: `"PARID"` not `PARID`
`Access denied: Not authorized to call function`	Used CAST/ROUND/AVG	Remove function, process client-side
Timeout / no response	Query too large	Add `LIMIT`, narrow `WHERE` clause
Empty results	Filter mismatch	Check exact string values with a broad query first
"resource not found"	Wrong resource ID	Use `resources <dataset>` to get correct ID

SQL Tips

Quote UPPERCASE column names — PostgreSQL is case-sensitive:

SELECT "PROPERTYADDRESS" FROM @assessments  -- ✓ uppercase needs quotes
SELECT case_year FROM @overdoses            -- ✓ lowercase works without quotes

GROUP BY works, but not aggregate functions:

SELECT "PROPERTYCITY", COUNT(*) as cnt 
FROM @assessments 
GROUP BY "PROPERTYCITY" 
ORDER BY cnt DESC 
LIMIT 10

Check fields first — Column names vary wildly between datasets

Coverage Map (Critical!)

Dataset	Coverage	Municipalities
Property Assessments	All Allegheny County	130 municipalities
Property Sales	All Allegheny County	130 municipalities
Fatal Overdoses	All Allegheny County	By zip code
Jail Census	All Allegheny County	County facility
911 Dispatches	Most of county	111 of 130 municipalities
Air Quality	All Allegheny County	Monitor locations
PLI Violations	City of Pittsburgh ONLY	90 neighborhoods
PLI Permits	City of Pittsburgh ONLY	90 neighborhoods
311 Requests	City of Pittsburgh ONLY	90 neighborhoods

If someone asks about Fox Chapel, Aspinwall, Mt. Lebanon, etc. → Only county-wide datasets apply. No PLI/311 data for suburbs.

Organizations & Topics

Use orgs and groups commands to explore. Major publishers:

allegheny-county (143 datasets) — assessments, health, jail
city-of-pittsburgh (126 datasets) — 311, permits, violations

Example Queries

# Property lookup by parcel ID
<skill>/wprdc.py parcel 0028F00194000000

# Search by address (use SQL)
<skill>/wprdc.py query 'SELECT * FROM @assessments WHERE "PROPERTYHOUSENUM"='"'"'251'"'"' AND "PROPERTYADDRESS" LIKE '"'"'%PASADENA%'"'"''

# Overdose trends by year
<skill>/wprdc.py query 'SELECT case_year, COUNT(*) as deaths FROM @overdoses GROUP BY case_year ORDER BY case_year'

# Filter by neighborhood (City of Pittsburgh only)
<skill>/wprdc.py query 'SELECT "VIOLATION", COUNT(*) FROM @violations WHERE "NEIGHBORHOOD"='"'"'Hazelwood'"'"' GROUP BY "VIOLATION" ORDER BY COUNT(*) DESC LIMIT 10'

# Cross-tab query
<skill>/wprdc.py query 'SELECT combined_od1, race, COUNT(*) FROM @overdoses GROUP BY combined_od1, race ORDER BY COUNT(*) DESC LIMIT 20'

Known Issues (as of Jan 2026)

311 Data stopped updating Feb 2025 — new system transition
County Plumbing Inspections — under maintenance
County Housing Inspections — under maintenance
County Food Facilities — under maintenance

Always run info <dataset> to check last update date before relying on data.

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add diegosouzapw/awesome-omni-skill/skills/data-ai/wprdc -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

92 / 100

Verified

未声明 license/许可。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
diegosouzapw/awesome-omni-skill
Version: 1.1.0
中文

More by @diegosouzapw

Category & tags

Category AI

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

WPRDC - Pittsburgh Regional Data Center

Quick Start

Commands

search <query>

info <dataset>

resources <dataset>

fields <resource>

query <sql>

parcel <pin>

download <dataset>

orgs

groups

shortcuts

Query Shortcuts

Before Querying, Ask Yourself

NEVER Do

Common Errors

SQL Tips

Coverage Map (Critical!)

Organizations & Topics

Example Queries

Known Issues (as of Jan 2026)

Discussion

`search <query>`

`info <dataset>`

`resources <dataset>`

`fields <resource>`

`query <sql>`

`parcel <pin>`

`download <dataset>`

`orgs`

`groups`

`shortcuts`