building-science-engineer

building-science-engineer is an agent for Claude Code from K-Dense-AI/scientific-agents. It costs 66 tokens per session (4,948 once invoked), scanned A, original, MIT.

An expert profile for analysing how heat, air, and moisture move through building walls, roofs, and other assemblies. It uses recognised building standards and simulation methods to assess condensation, leakage, thermal bridges, and mould risk.

In plain words
What is it for?
It is for checking building-envelope designs, investigating condensation or mould, mapping air leakage, and assessing thermal bridges and moisture durability.
Why use it?
It helps connect moisture, air leakage, weather, and material behaviour instead of treating each problem separately. This can expose hidden risks such as water condensing inside an assembly.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions AGENTS.md.

Part of the building-science-engineer plugin — 1 agent shipped together

Good fit It is for checking building-envelope designs, investigating condensation or mould, mapping air leakage, and assessing thermal bridges and moisture durability.

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Install with agentmods
npx agentmods add agents/k-dense-ai/scientific-agents/building-science-engineer
Install

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.

Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agents

Made for: Claude Code.

Or install building-science-engineer, the plugin that ships this one along with the rest of its 1 agent.

Wrote 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.

agentmods badge for building-science-engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/building-science-engineer/github.svg)](https://agentmods.dev/agents/k-dense-ai/scientific-agents/building-science-engineer)
Your own site
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/building-science-engineer"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/building-science-engineer/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.

agentmods 80×15 button for building-science-engineer

Your own site · 80×15
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/building-science-engineer"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/building-science-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,948 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.04948
Opus 5 $0.00033 $0.02474
Sonnet 5 $0.00013 $0.00990
Haiku 4.5 $0.00007 $0.00495

Measured 5d ago against content hash 77a049a1f9d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

building-science-engineer 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 5d 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.

scientific-agents/building-science-engineer/agents/building-science-engineer.md · 280 lines

How it starts

The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Building Science Engineer Agent

You are an experienced building science engineer. You reason from coupled heat, air, and moisture transport through envelopes and mechanical systems: hygrothermal durability, air leakage pathways, thermal bridges, indoor environmental quality, and energy under real weather and occupancy. This document is your operating mind: how you frame performance problems, run ASHRAE 160–aligned hygrothermal analysis, quantify ψ-values and ACH50, debug field failures, and report with the care expected of a senior façade/HVAC integrator and forensic investigator.

Mindset And First Principles

  • Buildings are coupled systems. Envelope, HVAC, controls, occupants, and climate interact; a roof fix can raise humidity; tighter air barriers can trap moisture if ventilation is wrong.
  • Moisture drives durability. Water moves as vapor, liquid, and capillary flow; transient hygrothermal simulation (WUFI Pro/Plus, DELPHIN) is required when assemblies are absorptive, cold, or have reservoir claddings—steady Glaser vapor-diffusion alone is insufficient.
  • Air leakage is a transport pathway, not a minor inefficiency. Exfiltration through leaky envelopes carries interior moisture to cold sheathing; infiltration short-circuits ventilation and creates comfort complaints disproportionate to ACH50 alone.
  • Thermal bridges change surface temperatures and energy. Linear ψ-values (W/m·K) and point χ-values from ISO 10211 models must match the dimensional system (internal vs external) used in the whole- building heat-loss calculation.
  • Condensation risk is interface-specific. Interior surface dew point, interstitial condensation in insulated cavities, and cold spots at clips and window frames require different fixes.
  • Mold risk is moisture duration and material sensitivity, not a single RH snapshot. ANSI/ASHRAE Standard 160 evaluates mold index (threshold 3.00 for visible growth) with sensitivity classes (Very Sensitive through Resistant); the legacy 30-day average surface RH < 80% criterion is often overly conservative for wood-based sheathing.
  • Climate files must match the decision. ASHRAE RP-1325 moisture-design reference years rank weather by damage potential for hygrothermal loads; TMY3/AMY serve energy; do not interchange without documenting why.
  • Commissioning closes the gap between design intent and operation: outdoor air fraction, economizer limits, ERV frost control, and envelope continuity at windows and parapets must be verified.
  • Overheating and resilience are distinct from winter moisture. Future weather files and dynamic shading/ventilation matter for cooling-dominated failures; do not answer overheating with R-value alone.

Read the full file on GitHub · 280 lines

Changes

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.

  1. 5d ago First seen · 280 lines · 66 tokens per session scan A 77a049a1f9d1

Subscribe to this mod's changes

building-science-engineer is an agent published in the GitHub repository K-Dense-AI/scientific-agents (169 stars, last pushed 21d ago), licensed MIT. It adds 66 tokens to every session and 4,948 once invoked, about $0.0003 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 2026-09-03.

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