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-pharmacovigilancegit 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-pharmacovigilance)<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-pharmacovigilance"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-pharmacovigilance/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-pharmacovigilance"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-pharmacovigilance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00096 | $0.04704 |
| Opus 5.5 | $0.00038 | $0.01882 |
| Sonnet 5.5 | $0.00019 | $0.00941 |
| Haiku 4.5 | $0.00010 | $0.00470 |
Grade A, and why
tooluniverse-pharmacovigilance 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 10d 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 — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Pharmacovigilance Safety Analyzer
Systematic drug safety analysis using FAERS adverse event data, FDA labeling, PharmGKB pharmacogenomics, and clinical trial safety signals.
KEY PRINCIPLES:
- Report-first approach - Create report file FIRST, update progressively
- Signal quantification - Use disproportionality measures (PRR, ROR)
- Severity stratification - Prioritize serious/fatal events
- Multi-source triangulation - FAERS, labels, trials, literature
- Pharmacogenomic context - Include genetic risk factors
- Actionable output - Risk-benefit summary with recommendations
- English-first queries - Always use English drug names in tool calls
When to Use
Apply when user asks:
- "What are the safety concerns for [drug]?"
- "What adverse events are associated with [drug]?"
- "Is [drug] safe? What are the risks?"
- "Compare safety profiles of [drug A] vs [drug B]"
- "Pharmacovigilance analysis for [drug]"
Clinical Reasoning Framework
Reasoning Strategy 1: On-Target vs Off-Target Thinking
Ask: is this adverse effect a predictable extension of the drug's mechanism (on-target), or something the mechanism doesn't explain (off-target)? On-target effects are dose-dependent and predictable. Off-target effects are often idiosyncratic and harder to predict.
How to apply this:
- Look up the drug's primary mechanism of action (use ChEMBL or DailyMed label)
- For each reported adverse event, ask: "Does this follow logically from what the drug does to its target?" If yes, it is on-target toxicity — expect dose-dependence and manage with dose reduction
- If the adverse event cannot be explained by the primary mechanism, consider off-target receptor binding or reactive metabolite formation. These require different management (drug discontinuation, not dose adjustment)
- Use KEGG pathway data to identify metabolic routes that could produce toxic intermediates
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago Changed · +17 lines · +20 tokens per session 1cc1349b5ced
- 1mo ago First seen · 334 lines · 76 tokens per session scan A bfb61e56402e
tooluniverse-pharmacovigilance is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,744 stars, last pushed yesterday), licensed Apache-2.0. It adds 96 tokens to every session and 4,704 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 2026-09-03.
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