What makes Ifc Qto Extraction notable?

1.2K downloads. Trust evidence available

How should Ifc Qto Extraction be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Ifc Qto Extraction

Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting. Skill: Ifc Qto Extraction Owner: datadrivenconstruction Summary: Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting. Tags: latest:2.0.0 Version history: v2.0.0 | 2026-02-13T16:07:11.073Z | auto Major update: Adds structured quantity extraction from IFC/Revit models, grouped reporting, and Python API. - Automated

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.2k

Updated

Oct 11, 2026

Version

2.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.2K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.2K downloadsadoption · observed Oct 11, 2026
Latest release: 2.0.0release · observed Feb 13, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1774mv3t1cm8r1kgs9hccdnmn8852nb:ifc-qto-extraction

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-datadrivenconstruction-ifc-qto-extraction/snapshot"

Documentation

CLAWHUB

44,059 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
name: "ifc-qto-extraction"
description: "Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting."
---

# IFC Quantity Takeoff Extraction

Extract structured quantity data from BIM models (IFC, Revit) for cost estimation, material ordering, and progress tracking.

## Business Case

**Problem**: Manual quantity takeoff is:
- Time-consuming (40-80 hours for medium project)
- Error-prone (human counting mistakes)
- Not repeatable (changes require full rework)
- Disconnected from design (no live updates)

**Solution**: Automated QTO from BIM that:
- Extracts all quantities in minutes
- Groups by type, level, zone
- Updates instantly with model changes
- Exports to Excel for pricing

**ROI**: 90% reduction in QTO time, near-zero counting errors

## DDC Tools Used

```
┌──────────────────────────────────────────────────────────────────────┐
│                      QTO EXTRACTION PIPELINE                          │
├──────────────────────────────────────────────────────────────────────┤
│                                                                       │
│   INPUT                 CONVERT                 ANALYZE               │
│   ┌─────────┐          ┌─────────┐            ┌─────────┐            │
│   │ .rvt    │          │ DDC     │            │ Python  │            │
│   │ .ifc    │─────────►│Converter│───────────►│ pandas  │            │
│   │ .dwg    │          │         │            │         │            │
│   └─────────┘          └─────────┘            └─────────┘            │
│                              │                      │                 │
│                              ▼                      ▼                 │
│                        ┌─────────┐            ┌─────────┐            │
│                        │ .xlsx   │            │ Grouped │            │
│                        │ raw data│            │ QTO     │            │
│                        └─────────┘            └─────────┘            │
│                                                    │                  │
│   OUTPUT                                           ▼                  │
│   ┌─────────────────────────────────────────────────────────────┐   │
│   │  QTO Report                                                  │   │
│   │  • Element counts by type                                    │   │
│   │  • Areas (m², ft²)                                           │   │
│   │  • Volumes (m³, ft³)                                         │   │
│   │  • Lengths (m, ft)                                           │   │
│   │  • Weights (kg, tons)                                        │   │
│   │  • Grouped by level/zone/system                              │   │
│   └─────────────────────────────────────────────────────────────┘   │
│                                                                       │
└─────────────

_meta.json

{
  "ownerId": "kn75fhjxn1jz5xbgd9ggj0nrtd80q1dz",
  "slug": "ifc-qto-extraction",
  "version": "2.0.0",
  "publishedAt": 1770998831073
}

instructions.md

You are a BIM quantity takeoff assistant. You extract structured quantity data from BIM models (IFC, Revit) for cost estimation, material ordering, and progress tracking.

When the user asks to extract quantities from a BIM model:
1. Identify the model format (.ifc or .rvt) and conversion method
2. For IFC: use IfcOpenShell to parse elements and extract properties
3. For Revit: use DDC RvtExporter to convert to structured data
4. Extract key quantities: count, area (m2), volume (m3), length (m), weight (kg)
5. Group results by category, type, level, and material
6. Export to Excel or CSV with pivot-ready structure

When the user asks to analyze QTO results:
1. Summarize totals by element category (walls, floors, columns, etc.)
2. Show material breakdown (concrete volume, steel weight, etc.)
3. Compare quantities across building levels
4. Flag elements with missing or zero quantities

## Input Format
- BIM model file path (.ifc or .rvt)
- Optional: specific element categories to extract
- Optional: grouping preferences (by level, category, material)

## Output Format
- QTO table: category, type, level, count, area, volume, length, material
- Summary by category with totals
- Material summary (total concrete, steel, etc.)
- Excel export with multiple sheets (Summary, Detail, By Level, By Material)

## Supported Properties
| Property | Unit | Source |
|----------|------|--------|
| Count | pcs | Element instances |
| Area | m2 | Surface/floor area |
| Volume | m3 | Solid geometry |
| Length | m | Linear elements |
| Weight | kg | Material density x volume |
| Perimeter | m | Floor/wall perimeter |

## Constraints
- Filesystem permission required for reading BIM files and writing exports
- IFC parsing uses IfcOpenShell (Python library, no external services)
- Revit conversion uses DDC RvtExporter CLI tool via subprocess
- Always validate that extracted quantities are non-negative
- Flag elements with no geometry or zero quantities

claw.json

{
  "name": "ifc-qto-extraction",
  "version": "2.0.0",
  "description": "Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.",
  "author": "datadrivenconstruction",
  "license": "MIT",
  "permissions": ["filesystem"],
  "entry": "instructions.md",
  "tags": ["construction", "IFC", "BIM", "quantity-takeoff", "QTO", "Revit", "estimation"],
  "models": ["claude-*", "gpt-*"],
  "minOpenClawVersion": "0.8.0"
}

Github ReposUpdated 1d agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.