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 human_protein_atlas_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/human_protein_atlas_database)<a href="https://agentmods.dev/skills/google-deepmind/science-skills/human_protein_atlas_database"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/human_protein_atlas_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/human_protein_atlas_database"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/human_protein_atlas_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 | $0.00033 | $0.01644 |
| Opus 5 | $0.00016 | $0.00822 |
| Sonnet 5 | $0.00007 | $0.00329 |
| Haiku 4.5 | $0.00003 | $0.00164 |
Grade A, and why
human-protein-atlas-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 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Human Protein Atlas (HPA) Database Integration
This skill provides semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA). While RNA-seq (e.g., GTEx) tells us if a gene is being transcribed, HPA confirms if the protein product actually exists, where it is located within the cell (e.g. nucleus vs cytoplasm), and its concentration in systemic blood circulation. The data is based on Immunohistochemistry (IHC) across normal human tissues and cancer types.
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/human_protein_atlas_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.proteinatlas.org/about/licence, then (2) create the file recording the notification text and timestamp.
When to Use
Use this skill when you need to:
- Map a gene symbol to its Ensembl ID for HPA queries.
- Retrieve the semi-quantitative protein abundance in normal human tissues and cancer types based on IHC staining (High, Medium, Low, or Not Detected).
- Find the specific organelles or subcellular structures where a protein has been localized (e.g., nucleoplasm, mitochondria).
- Check the consistency/agreement between RNA-seq consensus and protein expression levels.
- Search for genes based on specific protein expression criteria (e.g., "elevated in amygdala" or "secreted proteins").
Do NOT use when you need to:
- Query eQTLs, pQTLs, or any variant-level associations. HPA provides wild-type expression data and knows nothing about QTLs.
- Query gene expression in non-human species. HPA is strictly for human proteins.
- Retrieve purely quantitative RNA expression without interest in the protein product (consider using the GTEx skill instead).
Command Selection Guide
What ships with it
3 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.
- 11d ago First seen · 182 lines · 33 tokens per session scan A 35f990cd2348
human-protein-atlas-database is a skill published in the GitHub repository google-deepmind/science-skills (2,990 stars, last pushed 2d ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,644 once invoked, about $0.0002 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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