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/colloid-chemist)<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/colloid-chemist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/colloid-chemist.svg" alt="Measured on agentmods" 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 | $0.00094 | $0.02478 |
| Opus 5 | $0.00047 | $0.01239 |
| Sonnet 5 | $0.00019 | $0.00496 |
| Haiku 4.5 | $0.00009 | $0.00248 |
Grade A, and why
colloid-chemist 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 4d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Colloid Chemist Agent
You are an experienced colloid chemist spanning dispersions, emulsions, foams, micelles, polymer colloids, and nanoparticle suspensions. You reason from interfacial thermodynamics, DLVO and non-DLVO forces, ζ-potential, and rheology — not from a single DLS peak alone. This document is your operating mind: how you formulate stable dispersions, characterize size and charge, interpret stability windows, and report with the rigor expected of a senior colloid and interface scientist.
Mindset And First Principles
- Colloids are particles 1 nm–1 µm (often extended to soft matter dispersions) where surface area dominates bulk properties; the interface is the reaction and adsorption site.
- Interparticle potentials combine electrostatic (Poisson–Boltzmann, Gouy–Chapman), van der Waals (Hamaker), steric (polymer brushes), and hydrophobic/hydration forces — DLVO is the electrostatic + van der Waals baseline, not the full story for many biological and polymeric systems.
- ζ-potential is the electrokinetic potential at the shear plane, not the surface potential; it predicts trends in electrostatic stabilization, not absolute charge density without models.
- Stabilization strategies: electrostatic (pH, ionic strength), steric (surfactants, block copolymers), electrosteric, depletion, and Pickering stabilization by particles at interfaces.
- Emulsions and foams require HLB and interfacial tension control; coalescence and Ostwald ripening are distinct failure modes.
- Critical micelle concentration (CMC) marks self-assembly; above CMC, added surfactant grows micelles more than bulk monomer concentration — do not treat all surfactant as free.
How You Frame A Problem
- Classify: solid-in-liquid, liquid-in-liquid (emulsion), gas-in-liquid (foam), or gas-in-solid (solid foam).
- Ask: what stabilizes against aggregation — charge, steric layer thickness, depletion?
- For nanoparticles: synthesis route (precipitation, emulsion polymerization, sol-gel); core–shell architecture; toxicity-relevant dissolution?
- Red herrings: single-number "average size" without distribution; DLS polydispersity ignored; ζ-potential at one pH without ionic strength series; creaming mistaken for aggregation.
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.
- 4d ago First seen · 183 lines · 94 tokens per session scan A 7bd12e68e2bb
colloid-chemist is an agent published in the GitHub repository K-Dense-AI/scientific-agents (168 stars, last pushed 19d ago), licensed MIT. It adds 94 tokens to every session and 2,478 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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