ToolUniverse is a collection of tools, interfaces, and supporting components for building AI systems that perform scientific work. It is for developers creating AI scientist agents that use APIs, databases, machine-learning tools, and domain-specific utilities. The catalogue includes skills, commands, an MCP server, an agent, and a hook for working with the ecosystem.
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 mims-harvard/ToolUniverse --skill tooluniverse-electron-microscopygit clone --depth 1 https://github.com/mims-harvard/ToolUniverseWrote 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/mims-harvard/tooluniverse/tooluniverse-electron-microscopy)<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-electron-microscopy"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-electron-microscopy/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/mims-harvard/tooluniverse/tooluniverse-electron-microscopy"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-electron-microscopy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.03831 |
| Opus 5 | $0.00044 | $0.01916 |
| Sonnet 5 | $0.00018 | $0.00766 |
| Haiku 4.5 | $0.00009 | $0.00383 |
Grade A, and why
tooluniverse-electron-microscopy 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 11d 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Electron Microscopy Structure Analysis
Pipeline for discovering and analyzing electron microscopy data across the full resolution spectrum: from 3D density maps (EMDB) to fitted atomic models (PDB), raw micrograph datasets (EMPIAR), and cryo-electron tomography volumes (CryoET Data Portal). Connects EM data to structural biology context via PDB and AlphaFold.
Guiding principles:
- Resolution awareness -- always report and interpret map resolution; sub-4A enables atomic modeling, 4-8A enables domain fitting, >8A is shape-level
- Map before model -- the density map is the primary experimental data; fitted models are interpretations
- Method matters -- single particle analysis, tomography, 2D crystallography, and helical reconstruction have different strengths and limitations
- Raw data value -- EMPIAR raw data enables reprocessing with newer algorithms; always note availability
- Cross-reference structures -- connect EMDB maps to PDB entries and AlphaFold predictions for completeness
- English-first queries -- use English terms in tool calls
EM resolution determines what you can see. TEM resolves individual protein complexes (~2nm). Cryo-EM achieves near-atomic resolution (<4Å) for large complexes. SEM shows surface topology. Choose the right EM modality for the question.
LOOK UP, DON'T GUESS
When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory. A database-verified answer is always more reliable than a guess.
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
When to Use
Typical triggers:
- "Find cryo-EM structures of [protein/complex]"
- "What EMDB maps are available for [target]?"
- "Get raw micrograph data for [structure]"
- "Find tomography datasets for [organelle/cell type]"
- "What is the resolution of [EMDB entry]?"
- "Cross-reference this EM map with PDB models"
- "Find cryo-ET datasets for [sample]"
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.
- 11d ago First seen · 295 lines · 88 tokens per session scan A d145e5008fc3
tooluniverse-electron-microscopy is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed yesterday), licensed Apache-2.0. It adds 88 tokens to every session and 3,831 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 2026-08-30.
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