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AlpacaLabsLLC

Official

@alpacalabsllc

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2Public Repos
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36Published Skills

Offers specialized data extraction and regulatory analysis for architecture, engineering, and construction professionals managing complex building projects.

Skills Distribution
DomainBusiness, Fi...Architecture & Urb.. (40%)Construction Speci.. (30%)Real Estate Data A.. (30%)

Agent Skills by AlpacaLabsLLC

Showing 36 vetted skills indexed across 1 GitHub repositories.

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epd-compare

Compare environmental impacts across products and generate markdown reports.

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Advanced
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epd-research

Search EPD registries and rank candidates by GWP for material briefs.

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Intermediate
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epd-parser

Parse Environmental Product Declaration PDFs into a structured 42-column dataset.

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Advanced
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epd-to-spec

Generate CSI-formatted specification sections with GWP thresholds from EPD materials.

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Advanced
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studio

Route user input to the appropriate architecture AI agent or skill.

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Basic
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skills-menu

List all available skills and agents organized by domain.

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Basic
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nyc-dob-violations

Resolve NYC buildings by address, BBL, or BIN and summarize DOB and ECB violations.

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Intermediate
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nyc-dob-permits

Resolve NYC property data by retrieving DOB permits and job filings across Legacy BIS and DOB NOW datasets.

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Advanced
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nyc-bsa

Query BSA variances and special permits for NYC properties by address, BBL, or BIN.

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Advanced
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nyc-property-report

Consolidate six NYC Open Data lookups into a markdown property report.

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Advanced
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nyc-landmarks

Determine NYC landmark status and historic district information from an address, BBL, or BIN.

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Intermediate
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nyc-acris

Aggregate NYC ACRIS deeds, mortgages, and parties by address, BBL, or BIN.

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Advanced
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nyc-hpd

Resolve addresses to BBL or BIN and query NYC HPD housing datasets.

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Intermediate
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slide-deck-generator

Generate self-contained HTML slide decks from topics, outlines, or data.

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Advanced
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color-palette-generator

Generate 8-12 color palettes from descriptions, moods, or images into HTML.

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Advanced
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product-enrich

Infer and standardize FF&E product category, color, material, and style tags from CSV or Google Sheets inputs.

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Advanced
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product-spec-bulk-cleanup

Normalize FF&E schedules into a canonical cleaned dataset.

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Advanced
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product-spec-bulk-fetch

Extract FF&E product specifications from URLs into a 33-column Google Sheet or CSV.

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Advanced
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ffe-schedule

Generate standardized 33-column FF&E schedules from unstructured product data.

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Advanced
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product-spec-pdf-parser

Extract structured FF&E data from PDF product specs into a 33-column master schema.

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Advanced
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csv-to-sif

Convert CSV or Excel FF&E product lists into SIF files.

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Advanced
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product-research

Parse designer briefs, search web sources, and write FF&E shortlists to Google Sheets.

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Intermediate
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sif-to-csv

Parse SIF records, normalize manufacturer codes, and compute pricing to CSV or Google Sheets.

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Advanced
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product-pair

Analyze input product data and generate 5-8 complementary pairings with design reasoning.

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Intermediate

Frequently Asked Questions About AlpacaLabsLLC

FAQPage Schema
What specific tasks can I perform using these architectural and construction capabilities?

You can perform automated parsing of Environmental Product Declarations, generate CSI-aligned specification sections, calculate building occupancy loads per IBC standards, and aggregate complex NYC property datasets including zoning, permits, and historic landmark status.

Which professional personas benefit most from these technical capabilities?

These capabilities are designed for architects, interior designers, urban planners, and real estate developers who require rapid synthesis of building codes, material specifications, and municipal property records for project feasibility and documentation.

What are the primary prerequisites for running these data processing functions?

Users must provide source documentation such as PDF product specifications, CSV/Excel FF&E schedules, or specific site addresses/BBL/BIN identifiers for NYC-based property queries to trigger the underlying data extraction and synthesis logic.