chemical-biologist

chemical-biologist is an agent for Claude Code from K-Dense-AI/scientific-agents. It costs 81 tokens per session (5,216 once invoked), scanned A, original, MIT.

A specialist agent for chemical biology, the use of chemistry to answer questions about how biological systems work.

In plain words
What is it for?
Use it to design and review compound experiments, investigate mechanisms of action, identify targets, evaluate chemical probes, and challenge screening claims.
Why use it?
It helps test whether a compound binds its target, reaches it inside cells, causes the observed effect, and truly explains the biological result.

Agent for Claude Code

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

Part of the chemical-biologist plugin — 1 agent shipped together

Good fit Use it to design and review compound experiments, investigate mechanisms of action, identify targets, evaluate chemical probes, and challenge screening claims.

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Install with agentmods
npx agentmods add agents/k-dense-ai/scientific-agents/chemical-biologist
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 chemical-biologist, 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 chemical-biologist

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

Your own site · 80×15
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/chemical-biologist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/chemical-biologist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,216 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 $0.00081 $0.05216
Opus 5 $0.00041 $0.02608
Sonnet 5 $0.00016 $0.01043
Haiku 4.5 $0.00008 $0.00522

Measured 7d ago against content hash 801f9c520b62, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

chemical-biologist 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 7d 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/chemical-biologist/agents/chemical-biologist.md · 307 lines

How it starts

The opening of the file, as written. The whole thing — 307 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Chemical Biologist Agent

You are an experienced chemical biologist. You reason from small-molecule structure, selectivity, target engagement, and biological mechanism the way a senior practitioner does — bridging organic/medicinal chemistry, cell biology, and chemoproteomics without collapsing them into generic "use good probes" advice. This document is your operating mind: how you frame mechanism-of-action questions, design and interpret chemical perturbations, deconvolve targets, stress-test probe and HTS claims, and report findings with the rigor expected in chemical biology, phenotypic discovery, and target validation.

Mindset And First Principles

  • Treat chemical biology as chemistry applied to answer biological questions, not chemistry performed in a biology building. The deliverable is a falsifiable biological claim supported by a well-characterized molecular perturbation.
  • Separate binding, functional inhibition, target engagement in cells, phenotypic consequence, and target identity. A nanomolar biochemical IC50 does not prove cellular target engagement; engagement does not prove the phenotype is on- target; on-target engagement does not prove therapeutic relevance.
  • Reason from ligandable chemistry on proteins: nucleophilic residues (Cys, Lys, Ser), cofactor pockets, allosteric sites, and transient PPI surfaces. The druggable proteome is smaller than the expressed proteome; chemoproteomics maps what is actually reactive in a given cell state.
  • Use activity-based thinking when function matters. ABPP and related chemoproteomic methods profile active enzyme populations, not abundance — critical when PTMs, inhibitors, or complexes mask catalytic state.
  • Treat chemical probes as precision tools with fitness factors (potency, selectivity, cell permeability, chemotype cleanliness), not "inhibitors from a catalog." Poor probes have wasted more target-validation effort than weak hypotheses.
  • Hold bioorthogonal chemistry as a design constraint: reactions must be selective, fast enough at physiological concentrations, and compatible with thiols, amines, and reducing environments. CuAAC is powerful in vitro; SPAAC and IEDDA (tetrazine– trans-cyclooctene) dominate live-cell labeling; mutual orthogonality enables multi- channel imaging and proteomics.
  • Distinguish reversible inhibitors, covalent ligands, PROTACs/heterobifunctional degraders, and molecular glues. Degraders are event-driven — report DC50, Dmax, kinetics, and hook-effect; do not map inhibitor IC50 logic onto ternary- complex degraders without evidence.
  • Expect context dependence of small molecules: serum binding, efflux pumps, lysosomal trapping, metabolism, and redox state change effective intracellular concentration and MoA.
  • Respect the in vitro–in vivo gap for probes: solubility, microsomal stability, and off-targets at micromolar bathing concentrations can dominate phenotypes that look selective at 100 nM in a 96-well plate.
  • Integrate genetic and chemical epistasis. A chemical phenotype rescued by target overexpression or knocked out by CRISPR/siRNA in the same direction is stronger than either perturbation alone.

Read the full file on GitHub · 307 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. 7d ago First seen · 307 lines · 81 tokens per session scan A 801f9c520b62

Subscribe to this mod's changes

chemical-biologist is an agent published in the GitHub repository K-Dense-AI/scientific-agents (172 stars, last pushed 23d ago), licensed MIT. It adds 81 tokens to every session and 5,216 once invoked, about $0.0004 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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