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 marcinfinitesimal533/Claude-skills-for-Computational-Designers --skill environmental-simulationgit clone --depth 1 https://github.com/marcinfinitesimal533/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/marcinfinitesimal533/claude-skills-for-computational-designers/environmental-simulation)<a href="https://agentmods.dev/skills/marcinfinitesimal533/claude-skills-for-computational-designers/environmental-simulation"><img src="https://agentmods.dev/badge/skills/marcinfinitesimal533/claude-skills-for-computational-designers/environmental-simulation/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/marcinfinitesimal533/claude-skills-for-computational-designers/environmental-simulation"><img src="https://agentmods.dev/badge/skills/marcinfinitesimal533/claude-skills-for-computational-designers/environmental-simulation.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 | $0.00033 | $0.12909 |
| Opus 5 | $0.00016 | $0.06455 |
| Sonnet 5 | $0.00007 | $0.02582 |
| Haiku 4.5 | $0.00003 | $0.01291 |
Grade A, and why
environmental-simulation 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 11d 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.
This is a copy
100% identical to environmental-simulation — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 1,095 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Environmental Simulation for AEC Computational Design
This skill provides a comprehensive reference for environmental performance simulation in the Architecture, Engineering, and Construction industry. It covers daylight analysis, solar radiation studies, energy modeling, computational fluid dynamics for wind, thermal comfort assessment, acoustic simulation, and the Ladybug Tools ecosystem that ties these workflows together within parametric design environments.
1. Performance-Driven Design Philosophy
Why Simulate Early
The single most consequential decision in building performance is made in the first five percent of the design timeline. Orientation, massing, window-to-wall ratio, and floor plate depth are locked in during concept design, yet their impact on energy consumption, daylight quality, and occupant comfort persists for the entire operational life of the building — typically 50 to 100 years.
Late-stage simulation is a diagnostic exercise. Early-stage simulation is a generative tool. The distinction matters because retrofitting performance into an already-resolved form is orders of magnitude more expensive than shaping the form around performance from the beginning.
Cost of late performance analysis:
| Stage where issue discovered | Relative cost to fix |
|---|---|
| Concept design | 1x (baseline) |
| Schematic design | 5x |
| Design development | 15x |
| Construction documents | 50x |
| Construction | 150x |
| Post-occupancy | 500x+ |
These multipliers are well-documented across the AEC industry and reflect the reality that changing a window-to-wall ratio on a sketch costs nothing, but changing it after curtain wall shop drawings are issued can cost hundreds of thousands of dollars.
Integration of Simulation into the Design Loop
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.
- 11d ago First seen · 1,095 lines · 33 tokens per session scan A 73545cbb64de
environmental-simulation is a skill published in the GitHub repository marcinfinitesimal533/Claude-skills-for-Computational-Designers (2 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 12,909 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to environmental-simulation, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
environmental-simulation
Daylight analysis, solar radiation, energy simulation, CFD wind analysis, thermal comfort, acoustic simulation, and the Ladybug Tools ecosystem for performance-driven AEC computational design.
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