Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Abhinavbwj/Claude-skills-for-Computational-Designers --skill design-automationgit clone --depth 1 https://github.com/Abhinavbwj/Claude-skills-for-Computational-DesignersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/abhinavbwj/claude-skills-for-computational-designers/design-automation)<a href="https://agentmods.dev/skills/abhinavbwj/claude-skills-for-computational-designers/design-automation"><img src="https://agentmods.dev/badge/skills/abhinavbwj/claude-skills-for-computational-designers/design-automation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/abhinavbwj/claude-skills-for-computational-designers/design-automation"><img src="https://agentmods.dev/badge/skills/abhinavbwj/claude-skills-for-computational-designers/design-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.10917 |
| Opus 5 | $0.00015 | $0.05458 |
| Sonnet 5 | $0.00006 | $0.02183 |
| Haiku 4.5 | $0.00003 | $0.01092 |
Grade A, and why
design-automation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- design-automation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 940 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Automation for AEC
Design automation is the disciplined application of computational logic to replace, accelerate, or augment repetitive and rule-governed design tasks across architecture, engineering, and construction. This skill covers the full spectrum from simple parametric rules through constraint-satisfaction engines to fully generative layout systems, drawing automation pipelines, and automated code-compliance verification.
1. Design Automation Spectrum
1.1 Levels of Automation in AEC
Design automation exists on a continuum. Understanding where a task falls on this spectrum determines the appropriate technology and the degree of human oversight required.
| Level | Label | Description | Example |
|---|---|---|---|
| 0 | Manual | Designer makes every decision, draws every line | Hand-drafted floor plans |
| 1 | Parametric | Geometry driven by explicit parameters; designer controls inputs | Grasshopper slider controlling facade panel width |
| 2 | Rule-Based | IF-THEN logic encodes design knowledge; system applies rules automatically | Auto-sizing exit widths based on occupant load |
| 3 | Constraint-Based | System searches solution space satisfying stated constraints | CSP solver placing rooms to satisfy adjacency + area constraints |
| 4 | Generative | System produces many candidate designs autonomously; human selects | GA-based floor plan generator producing 500 layout options |
| 5 | AI-Assisted | Machine-learned models propose designs or predict performance | GAN generating floor plan from adjacency graph |
| 6 | Autonomous | Fully closed-loop: sense conditions, generate design, validate, output | Automated site grading from survey to construction docs (emerging) |
1.2 What Can vs. Should Be Automated
High automation potential:
- Code compliance checking (deterministic rules)
- Structural member sizing (engineering formulas)
- Parking layout optimization (geometric + count)
- Sheet creation and annotation (repetitive)
- Clash detection (spatial intersection)
- Area and quantity takeoffs (data extraction)
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 940 lines · 31 tokens per session scan A b9f27b7b62fd
design-automation is a skill published in the GitHub repository Abhinavbwj/Claude-skills-for-Computational-Designers (212 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 10,917 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
design-automation
Rule-based design systems, constraint satisfaction, space planning algorithms, automated layout generation, drawing automation, code compliance checking, and computational workflows for AEC design automation.
taiyi-ui-design
A design-planning guide for describing how an application's user interface should look and behave. It produces a UI-DESIGN.md document covering layouts, components, interactions, accessibility, and error states.
taiyi-diagram-arch
A workflow for turning written system or product architecture into readable, version-controlled diagrams using Mermaid or exported SVG and PNG files. Architecture diagrams show components, boundaries, data flows, and deployment relationships.
taiyi-restyle
A planning guide for breaking a large user-interface redesign into smaller, independently reviewable tasks. A user interface is the part of an application that people see and use.
taiyi-diagram-pipeline
A pipeline that creates and updates architecture diagrams in three stages: a C4 model from the code, an engineering architecture diagram, and an exported PNG image. C4 is a way to describe software architecture at several levels of detail.
taiyi-diagram-render
A tool for rendering existing C4 or architecture Mermaid diagrams as SVG or PNG images. C4 is a way to show software systems at different levels, while Mermaid is a text format for diagrams.