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.
git 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/commands/mims-harvard/tooluniverse/verify-references)<a href="https://agentmods.dev/commands/mims-harvard/tooluniverse/verify-references"><img src="https://agentmods.dev/badge/commands/mims-harvard/tooluniverse/verify-references.svg" alt="Measured on agentmods" 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 | $0.00167 | $0.02515 |
| Opus 5 | $0.00084 | $0.01257 |
| Sonnet 5 | $0.00033 | $0.00503 |
| Haiku 4.5 | $0.00017 | $0.00251 |
Grade A, and why
verify-references 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.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verify these references: $ARGUMENTS
A citation that looks well-formed (real-sounding authors, a plausible journal, a DOI-shaped string) can still be wrong in three different ways: the paper doesn't exist at all (fabricated), the paper exists but the citation misstates it (wrong year, wrong journal, wrong authors), or the paper exists and is cited correctly but has since been retracted. Only a database lookup distinguishes these — don't judge a citation by how plausible it reads.
Process
1. Parse the input into individual entries
Figure out what you're checking before touching any tool:
- Single citation or claim ("Smith et al 2023 showed X, doi:10.1038/xyz") → one entry.
.bibfile → read it and parse each@article{key, title={...}, author={...}, year={...}, journal={...}, doi={...}}block into a record. Missing fields are fine — just note what wasn't stated.- Pasted reference list (numbered
[12] ..., or a References section from a paper draft) → split on the list's own numbering/formatting. Don't re-derive boundaries from prose; use whatever markers the list already uses.
For each entry, extract whatever is present: DOI, title, author(s), year, journal/venue. A DOI is the strongest anchor — resolve on that first when available. If two entries share the same DOI, resolve it once and reuse the record — don't repeat the same lookup.
2. Resolve each entry to an authoritative record
If a DOI is present:
tu run Crossref_get_work '{"doi":"10.1038/s41586-025-10014-0"}'
Crossref is the largest DOI registrar, not the only one — it covers most journal articles, but datasets, software, and many repository records (Zenodo, institutional archives) are registered with DataCite instead. A Crossref 404 on its own does not mean the DOI is fake; try DataCite before concluding that:
tu run DataCite_get_doi '{"doi":"10.5281/zenodo.1215979"}'
Only classify the DOI as fabricated/mistyped once both registries fail
(also try stripping trailing punctuation first — a stray period or
parenthesis from the citation's formatting is a common false negative).
Cross-check the returned title/authors/year against one more independent
source (openalex_get_work_by_doi or SemanticScholar_get_paper with
{"paper_id":"DOI:<doi>"}) — registry metadata is occasionally sparse for
older or unusual works.
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.
- 7d ago First seen · 183 lines · 167 tokens per session scan A 2c8e3a3c8a35
verify-references is a command published in the GitHub repository mims-harvard/ToolUniverse (1,672 stars, last pushed yesterday), licensed Apache-2.0. It adds 167 tokens to every session and 2,515 once invoked, about $0.0008 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.
Other commands, from other repositories
template
Manage issue templates for streamlined issue creation.
discover
Search the Everruns(Dev) API catalog for available operations.
swarm-status
Command documentation for swarm-status in category swarm.
archive-ledger
../../../shared/commands/archive-ledger.md.
real-time-view
Command "real-time-view" from dp-web4/SAGE, covering real-time-view, usage, options, examples and start real-time view.
research
Document codebase as-is with thoughts directory for historical context.