Science Skills is a collection of add-ons that give AI agents structured instructions, scripts, and references for scientific research, including genomics, structural biology, cheminformatics, and literature search. Researchers use it to guide agents through specialized scientific tasks with information from databases and tools such as AlphaGenome, AFDB, and UniProt. The catalogue entries are individual skills from this collection.
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 google-deepmind/science-skills --skill interpro_databasegit clone --depth 1 https://github.com/google-deepmind/science-skillsWrote 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/google-deepmind/science-skills/interpro_database)<a href="https://agentmods.dev/skills/google-deepmind/science-skills/interpro_database"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/interpro_database/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/google-deepmind/science-skills/interpro_database"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/interpro_database.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 | $0.00084 | $0.04198 |
| Opus 5.5 | $0.00034 | $0.01679 |
| Sonnet 5.5 | $0.00017 | $0.00840 |
| Haiku 4.5 | $0.00008 | $0.00420 |
Grade A, and why
interpro-database 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 1mo 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 — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.
InterPro Database Access
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/interpro_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ebi.ac.uk/interpro/ and https://www.ebi.ac.uk/about/terms-of-use/, then (2) create the file recording the notification text and timestamp.
Overview
InterPro combines signatures from multiple, diverse databases into a single searchable resource, reducing redundancy and helping users interpret their sequence analysis results. By uniting these member databases (e.g., Pfam, CDD, SMART), InterPro capitalises on their individual strengths to produce a powerful diagnostic tool and integrated resource.
Use interpro-database to:
- Identify what domains, families, and sites are found in a particular protein.
- Identify all proteins that belong to a protein family or contain a particular domain, even when the names and activities of the proteins are highly variable.
- Examine the species in which a particular protein family or domain is found.
- Annotate genomes with protein family information and Gene Ontology (GO) terms.
This skill provides a robust utility, interpro_client.py, to interact with the
InterPro API seamlessly. It natively handles rate limiting (HTTP 429),
background query sleep tracking (HTTP 408), terminal errors (HTTP 404/410), and
lazy pagination.
Core Rules
- Use the Wrapper: ALWAYS execute the
scripts/interpro_client.pyhelper script to query the database rather than accessing the database directly. The scripts automatically enforce fair use and implement retry logic. - For exploratory queries: ALWAYS use the CLI with a strict
--limit. This allows you to rapidly understand the data schema without polluting your context window or fetching millions of results. - Output to file: Use the CLI with --output to output to a file rather than attempting to print it all to the console. Process the output using jq or code.
- For more complex pipelines import the module natively into your Python scripts to consume the generator directly, preventing the need to deserialize CLI strings in large workflows.
- Notification: If this skill is used, ensure this is mentioned in the output.
What ships with it
4 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.
- 1mo ago First seen · 428 lines · 84 tokens per session scan A ab24b2241057
interpro-database is a skill published in the GitHub repository google-deepmind/science-skills (3,307 stars, last pushed 6d ago), licensed Apache-2.0. It adds 84 tokens to every session and 4,198 once invoked, about $0.0003 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 2026-08-30.
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