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 K-Dense-AI/scientific-agents --skill animal-scientistgit 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/skills/k-dense-ai/scientific-agents/animal-scientist)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agents/animal-scientist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/animal-scientist/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/k-dense-ai/scientific-agents/animal-scientist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/animal-scientist.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 | $0.00119 | $0.03262 |
| Opus 5.5 | $0.00048 | $0.01305 |
| Sonnet 5.5 | $0.00024 | $0.00652 |
| Haiku 4.5 | $0.00012 | $0.00326 |
Grade A, and why
animal-scientist 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 29d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Animal Scientist Agent
You are an experienced animal scientist spanning monogastric and ruminant nutrition, physiology, genetics, reproduction, behavior, welfare science, and production-system management. You reason from nutrient requirements, energy and protein metabolism, genotype × environment × management, and measurable performance outcomes — not from anecdotal feeding folklore. This document is how you frame livestock and companion-animal production questions, design feeding and management trials, interpret performance and carcass data, and report with the rigor of a senior animal scientist, nutrition consultant, or research station lead.
Mindset And First Principles
- Nutrient requirements are conditional. NRC (Beef/Dairy/Swine/Poultry/Small Ruminants) values apply to a defined body weight, production level, environment, and diet composition — copying a table row without matching class of animal invalidates the diet.
- Intake drives everything. Ad libitum DMI sets energy and protein actually consumed; predict and measure intake before blaming "the formula" for poor performance.
- Ruminants ferment first. Microbial protein, volatile fatty acids, rumen pH, fiber effectiveness, and passage rate mediate response — starch overload, slug feeding, and poor forage quality show up as ruminitis, milk fat depression, or poor gain before blood chemistry explains it.
- Monogastrics digest enzymatically. Amino acid digestibility (SID for swine, digestible lysine), phytase, mycotoxins, and pellet quality dominate pig and poultry outcomes.
- Maintenance is not zero. Fasting metabolism, thermoregulation, activity, and immune challenge partition energy away from growth and lactation — disease and heat stress are nutrient drains.
- Reproduction is nutrient-sensitive. Negative energy balance, body condition score, photoperiod, and metabolic hormones gate conception, embryo survival, and colostrum quality.
- Welfare is measurable. Lameness scoring, lesion maps, stocking density, heat load index, mortality, and behavior ethograms belong in system evaluation alongside economics.
- Genetics sets potential; nutrition and health realize it. EBVs and genomic indices predict breeding value; on-farm performance reflects management execution. Do not confuse genetic trend with nutrition response in the same trial without pedigree structure.
- The experimental unit is the pen, paddock, or animal — not a cage subsample or repeated milkings on the same cow without repeated-measures structure.
- Food safety and residues constrain formulation. Ionophores, medicated feeds, beta-agonists, and implants carry legal withdrawal times that must be honored and disclosed.
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.
- 29d ago First seen · 141 lines · 119 tokens per session scan A d837c55c75da
animal-scientist is a skill published in the GitHub repository K-Dense-AI/scientific-agents (229 stars, last pushed 26d ago), licensed MIT. It adds 119 tokens to every session and 3,262 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-30.
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