ml-for-aec SKILL.md skillB

ml-for-aec from marcinfinitesimal533/claude-skills-for-computational-designers is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add marcinfinitesimal533/claude-skills-for-computational-designers/ml-for-aec@v1.0.0

Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
B, 16 of 17 checks passed
Kind
SKILL.md skill
Repository
marcinfinitesimal533/claude-skills-for-computational-designers
Path
skills/ml-for-aec/SKILL.md
Versions recorded
1
Latest version
v1.0.0, committed Mar 26, 2026
Size
48,376 bytes
Repository stars
3
License
MIT

Computer vision for buildings, image-to-floorplan, generative ML models, performance prediction, structural analysis ML, energy prediction, natural language to design, and point cloud ML for AEC computational design.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Machine Learning for AEC

Machine learning is reshaping specific domains within Architecture, Engineering, and Construction, though the transformation is uneven. This skill provides a thorough, practitioner-oriented guide to where ML delivers real value in AEC today, the architectures and methods that work, the data challenges that constrain adoption, and practical pipelines for training, deploying, and maintaining ML models in production AEC workflows.

---

## 1. ML in AEC: Current State

### 1.1 Where ML Actually Works in AEC Today

ML in AEC is most effective where three conditions converge: (a) sufficient training data exists or can be generated, (b) the task is well-defined with measurable performance metrics, and (c) the cost of errors is manageable or human review is in the loop.

**Proven, deployed applications**:
- Construction progress monitoring (photo comparison to BIM schedule)
- Safety monitoring on construction sites (PPE detection, exclusion zones)
- Defect detection (crack detection in concrete, facade inspections via drone imagery)
- Document classification (sorting drawings by discipline, type)
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add marcinfinitesimal533/claude-skills-for-computational-designers/ml-for-aec@sha256:a482c233945f1f47

The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_jhq262vb25jiuknp.svg)](https://markdownregistry.com/a/art_jhq262vb25jiuknp)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Mar 26, 2026.

versioncommittedcommitsizeaudit
v1.0.0 latest2026-03-26 6dff3d2 48,376 BB view

Audit of the latest version

B  16 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • fail: Frontmatter declares a name
  • pass: Frontmatter block present
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (48376 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Starting a new one? Use a template for SKILL.md on mdpantry, which passes every one of these checks and says what to change in it.

Source

GitHub

marcinfinitesimal533/claude-skills-for-computational-designers · 3 stars · license MIT · pushed 2026-10-13 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_jhq262vb25jiuknp
GET https://markdownregistry.com/api/v1/resolve?ref=marcinfinitesimal533/claude-skills-for-computational-designers/ml-for-aec
GET https://markdownregistry.com/api/v1/blob/a482c233945f1f4719835d7908c0b733985eb5c0ae9e6a731c666ffc248e6f38

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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