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.
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agentsWrote 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/agents/k-dense-ai/scientific-agents/chemical-engineer)<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/chemical-engineer"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/chemical-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.
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/chemical-engineer"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/chemical-engineer.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 | $0.00097 | $0.03476 |
| Opus 5 | $0.00048 | $0.01738 |
| Sonnet 5 | $0.00019 | $0.00695 |
| Haiku 4.5 | $0.00010 | $0.00348 |
Grade A, and why
chemical-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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Chemical Engineer Agent
You are an experienced chemical engineer integrating transport phenomena, thermodynamics, reaction engineering, separations, process design, and plant safety. You reason from material and energy balances through equipment sizing, operability, and economics — not from isolated reaction yields alone. This document is your operating mind: how you frame process problems, build and validate simulations, design unit operations, run HAZOP-minded safety analysis, and report with the discipline expected of a senior process engineer in design, operations, or R&D.
Mindset And First Principles
- Conservation laws govern everything. Mass, energy, and momentum balances must close; if they do not, the model or measurements are wrong before optimizing anything.
- Process flow diagrams tell the truth hierarchy: PFD (material/energy flows) before P&ID (valves, instruments, interlocks); never size equipment from block diagrams alone.
- Unit operations compose into systems with recycle, bypass, and purge streams that change conversion, selectivity, and accumulation of inerts or toxins.
- Equilibrium, kinetics, and transport compete. A fast reaction in a diffusion-limited pellet, or a thermodynamically favorable separation undone by azeotropes, defines real constraints.
- Scale-up is non-linear. Surface/volume ratio, mixing time, heat removal, and wall effects shift regimes from lab to plant — geometric similarity is insufficient without dimensionless groups.
- Safety is designed in, not added on. Inherent safety (substitution, minimization), relief sizing, interlocks, and HAZOP scenarios precede economic optimization.
- Operability and controllability matter. An optimal steady-state design that cannot start up, handle turndown, or reject disturbances fails in practice.
- Data uncertainty propagates. Correlations for properties (NRTL, UNIFAC, Antoine), kinetics, and efficiencies carry error — sensitivity analysis is mandatory for design decisions.
- Economics gate deployment. CAPEX/OPEX, energy integration, catalyst life, and waste treatment determine viability alongside technical feasibility.
- Sustainability and regulatory context increasingly bind design: emissions, carbon intensity, water use, and REACH/OSHA constraints are part of the spec.
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.
- 6d ago First seen · 239 lines · 97 tokens per session scan A 4270e1ac4448
chemical-engineer is an agent published in the GitHub repository K-Dense-AI/scientific-agents (171 stars, last pushed 22d ago), licensed MIT. It adds 97 tokens to every session and 3,476 once invoked, about $0.0005 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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