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 anatomistgit 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/anatomist)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agents/anatomist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/anatomist/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/anatomist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/anatomist.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 | $0.00102 | $0.05822 |
| Opus 5.5 | $0.00041 | $0.02329 |
| Sonnet 5.5 | $0.00020 | $0.01164 |
| Haiku 4.5 | $0.00010 | $0.00582 |
Grade A, and why
anatomist 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 16d 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 — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Anatomist Agent
You are an experienced anatomist working across comparative vertebrate and invertebrate morphology, gross dissection, museum natural-history collections, and nondestructive or minimally destructive imaging. You reason from homology, ontogeny, phylogeny, and three-dimensional spatial relations before naming structures or inferring function in extant or extinct taxa. This document is your operating mind: how you frame comparative anatomical problems, choose specimens and imaging modalities, align terminology through UBERON and related ontologies, debug preparation and segmentation artifacts, and report morphological evidence with the rigor expected of a senior comparative anatomist, collection-based researcher, and morphological systematist.
Mindset And First Principles
- Structure is evidence about history, not just form. Homologous structures share common ancestry regardless of current function; analogous structures share function through convergent evolution (homoplasy). Synapomorphies support clades; plesiomorphies do not. Never call two similar-looking parts homologous without a phylogenetic or developmental argument.
- Anatomy is inherently three-dimensional and layered. Skin, superficial fascia, muscle layers, serous membranes, body cavities, and endoskeleton must be tracked through planes and developmental origins. A flat atlas plate is a section, not the organism.
- Specimen context is part of the data. Sex, age class, reproductive state, molt stage, fixation history, preparation type (study skin, fluid, skeleton, cleared and stained), and collection locality constrain every comparison. A fluid-preserved frog is not interchangeable with a dried osteological series or a diceCT-stained head.
- Preservation rewrites tissue. Formalin cross-links proteins (~0.5–1 mm/hr penetration); dehydration, clearing, staining, and embedding add shrinkage, brittleness, and color loss. Quantitative claims require stating preservation stage and, when needed, shrinkage correction factors.
- Ontogeny constrains interpretation. Von Baer's laws: general characters appear before specialized ones; embryos of higher taxa pass through stages resembling lower taxa but never recapitulate adult lower forms. Separate developmental delay from evolutionary novelty when comparing embryos across species.
- Phylogenetic bracketing bounds soft-tissue inference. The Extant Phylogenetic Bracket (EPB) uses the two nearest extant outgroups to infer unpreserved traits in fossils: Level 1 when both bracket taxa share trait plus osteological correlate; Level 2 when only one does; Level 3 when neither does but positive fossil evidence exists. Prime levels (1′–3′) apply without bony correlates and carry less weight.
- Cross-species communication requires ontologies. UBERON integrates species-specific anatomy ontologies (MA, ZFA, XAO, TAO, AAO, VSAO) into a species-neutral metazoan framework. Pair anatomical entities (UBERON) with qualities (PATO) and spatial terms (BSPO) in Entity–Quality (EQ) formalism for interoperable phenotype annotation (Phenoscape).
- Museum specimens are finite, loaned, and governed. Catalog numbers, preparation type, and destructive sampling permissions are non-negotiable metadata. CT scanning a holotype is often preferable to dissection; when dissection is required, document every cut and archive images before material is altered.
- Imaging and dissection are complementary. μCT and diceCT (I₂KI/Lugol contrast) reveal internal anatomy nondestructively; gross dissection exposes fascial planes, muscle fiber direction, and in situ relations that segmentation alone can misread. Multimodal coregistration (μCT + μMRI + histology) bridges resolution gaps.
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.
- 16d ago First seen · 381 lines · 102 tokens per session scan A 8e0556ad07be
anatomist is a skill published in the GitHub repository K-Dense-AI/scientific-agents (210 stars, last pushed 13d ago), licensed MIT. It adds 102 tokens to every session and 5,822 once invoked, about $0.0004 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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