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Drawing Quantity Extract

Organization
AlpacaLabsLLC
drawing-quantity-extract

Extract countable FF&E or luminaire instances from supplied drawings with position-level evidence. Use for plan quantities or symbol counts; not area takeoffs, product specs or cross-source reconciliation.

Overview

PublisherAlpacaLabsLLC
Repositoryskills-for-architects
Skill namedrawing-quantity-extract
Stars
386
Forks
81
Bundled files
1
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AlpacaLabsLLC on GitHub. Read the source before you install it.

Installation

Install the Drawing Quantity Extract AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AlpacaLabsLLC/skills-for-architects/tree/main/skills/drawing-quantity-extract
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architects.git /tmp/skills-for-architects
mkdir -p .claude/skills
cp -r /tmp/skills-for-architects/skills/drawing-quantity-extract .claude/skills/drawing-quantity-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Drawing Quantity Extract in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Drawing Quantity Extract on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Drawing Quantity Extract is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/as:drawing-quantity-extract — Count drawing instances

Before acting, read the host contract and declaration (skill:drawing-quantity-extract), using only referenced profiles from the catalog. Requirements do not grant access.

Use the host adapter and available native tools or ordinary task-specific code. Operation names identify semantic procedures, not installed functions. No Arch Studio runner, package installation or executable reconstruction is required. Existing exact authorization persists; ask only for material missing information or permission.

Input: exact supplied drawing files/revisions, building/floor/phase scope and requested tags/types. Output: unadopted instance ledger, scoped counts and coverage/exclusion evidence. No record owner is changed. Read owning instructions for project work; one-off files do not require initialization.

  1. Verify actual source access. Freeze document hashes and physical page list; record printed sheet IDs separately. Keep drawing types/revisions distinct. Missing access calls a real host grant or produces a precise handoff; never substitute another workspace.
  2. Read native evidence procedures. Extract text and coordinates using the native pdf_evidence.extract procedure; use host OCR/visual inspection for image-only labels. Save page-sized checkpoints. A legend index is local to its drawing, not a global type ID.
  3. Build one ledger row per candidate label/symbol at its document/page/bounding box. Classify each as instance, legend, note or unresolved. Count repeated identical tags at distinct positions; inspect duplicate text/OCR layers and overlapping boxes before excluding any. Preserve exclusions and reasons. Associate rooms only using visible boundaries or explicit schedule evidence, not nearest-label proximity.
  4. Inspect each scoped page against the ledger. Reconcile revision callouts and same-page schedules; never count note text as furniture or silently relabel instances because a revision note proposes it. Keep observed label counts and any evidenced revised allocation distinct. If methods disagree, report unresolved counts and the source regions; an approximate number is not verified quantity.
  5. Apply drawing_quantities.summarize with native computation under the complete evidence procedure. It counts supplied classified instances only. Retain the actual result plus the host's per-page coverage and visual evidence; neither a successful command nor unique-tag count proves full extraction.
  6. Return counts by exact tag and scope, source locators, excluded/unresolved instances and pages not inspected. Save only requested derived outputs, fresh-read them and preserve originals. Route comparison with inventories or other drawings to /as:schedule-quantity-reconcile; route adopted record changes to /as:master-schedule, under its authorization. Never certify procurement totals.

Current document placement

Save only authorized derived outputs and verify their actual content, source hashes and complete requested scope. Inline answers and one-off files need no project setup or adoption. For a requested registered project report, resolve confirmed coordinates using the receive-owned native documents.resolve/register semantics in the workspace model, including its complete document/register mutation sequence. Find existing records with documents.query; never guess a folder. This conditional handoff does not authorize schedule or library changes.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Drawing Quantity Extract AI skill do?

Extract countable FF&E or luminaire instances from supplied drawings with position-level evidence. Use for plan quantities or symbol counts; not area takeoffs, product specs or cross-source reconciliation.

Why use Drawing Quantity Extract on TypingMind?

Because you install it once and use it with any model. Drawing Quantity Extract is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Drawing Quantity Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlpacaLabsLLC/skills-for-architects/tree/main/skills/drawing-quantity-extract. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Drawing Quantity Extract?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Drawing Quantity Extract?

As many as you like. As long as a model supports skills, you can use Drawing Quantity Extract with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Drawing Quantity Extract AI skill free?

Yes. It is published on GitHub by AlpacaLabsLLC under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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