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Agent skill

Human Protein Atlas Database

by google-deepmind in google-deepmind/science-skills

A skill your agent uses when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

Apache-2.0Auto-check passedResearch & Science

Install Human Protein Atlas Database

skills CLI
$ npx skills add google-deepmind/science-skills --skill human-protein-atlas-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google-deepmind/science-skills human-protein-atlas-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/human_protein_atlas_database .claude/skills/human-protein-atlas-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
human-protein-atlas-database
GitHub stars
3.2k
Used in
2 other repos
Token cost
~1.6k tokens
SKILL.md length
705 words
Files
4 (incl. scripts, references)
Skills in repo
40
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

  • Works in 5 steps: resolve-ensembl-id — Gene Symbol →… → get-tissue-expression — Get Tissue… → get-subcellular-location — Get… → …
  • You want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA)
  • SKILL.md covers Prerequisites, When to Use, Command Selection Guide and Quick Start, plus 4 more sections
  • Runs Python scripts from its folder; calls uv

What it does

Human Protein Atlas Database is an agent skill from google-deepmind/science-skills. Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/search-api.md` and `scripts/hpa_cli.py`).

It sits in Research & Science, covering Internationalization. It works with Ensembl. The repository describes itself as: GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other… The licence is Apache-2.0.

When your agent uses it

  • You want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA)
  • Tasks that involve Internationalization

Example prompts

  • “/human-protein-atlas-database”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. resolve-ensembl-id — Gene Symbol → Ensembl ID
  2. get-tissue-expression — Get Tissue Protein Levels
  3. get-subcellular-location — Get Subcellular Location
  4. get-atlas-entry — Get Full HPA Entry
  5. search-hpa — Search by Attribute

What it can do on your machine

Read from SKILL.md and the folder at commit 6883275. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • proteinatlas.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Human Protein Atlas Database loads about 1.6k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 705 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from google-deepmind/science-skills at commit 6883275, republished under its Apache-2.0 licence (© google-deepmind). 705 words, ~1,607 tokens.

Download SKILL.mdSave it as .claude/skills/human-protein-atlas-database/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
human-protein-atlas-database
description
Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

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

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. 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

Pick the right command on the first try. Match the user's input to the correct subcommand below.

  • Map a gene symbol to Ensembl ID: resolve-ensembl-id
  • Get tissue protein expression levels: get-tissue-expression
  • Get subcellular location of a protein: get-subcellular-location
  • Get the full HPA metadata entry for a gene: get-atlas-entry
  • Search HPA for genes matching specific criteria: search-hpa

Quick Start

bash
# Map the ERBB2 gene symbol to its Ensembl ID
uv run scripts/hpa_cli.py resolve-ensembl-id ERBB2 --output /tmp/erbb2_id.json

# Get subcellular location by Ensembl ID
uv run scripts/hpa_cli.py get-subcellular-location ENSG00000141736 --output /tmp/erbb2_location.json

All subcommands write JSON to disk. Always save output in the /tmp/ directory. The default output file is /tmp/hpa_output.json if --output is not specified.

Commands

1. resolve-ensembl-id — Gene Symbol → Ensembl ID

Maps a common gene symbol (e.g., "TP53", "ERBB2") to its Ensembl gene ID. HPA endpoints are strictly Ensembl-based.

bash
uv run scripts/hpa_cli.py resolve-ensembl-id TP53 --output /tmp/tp53_id.json

Arguments:

  • gene_symbol (positional): The standard gene symbol (e.g., "TP53").
  • --output: Output file path (default: /tmp/hpa_output.json).
2. get-tissue-expression — Get Tissue Protein Levels

Returns a list of tissues and their corresponding protein expression levels (High, Medium, Low, or Not Detected) based on IHC staining.

bash
uv run scripts/hpa_cli.py get-tissue-expression ENSG00000130234 \
  --tissues "duodenum,thyroid gland" --output /tmp/tissue_expr.json

Arguments:

  • ensembl_id (positional): The Ensembl Gene ID.
  • --tissues: Comma-separated list of tissues to filter by (optional, defaults to all available tissues).
  • --output: Output file path (default: /tmp/hpa_output.json).
Show full SKILL.md (257 more words)Show less
3. get-subcellular-location — Get Subcellular Location

Retrieves the specific organelles or cellular structures where the protein has been localized.

bash
uv run scripts/hpa_cli.py get-subcellular-location ENSG00000141736 \
  --output /tmp/subcellular.json

Arguments:

  • ensembl_id (positional): The Ensembl Gene ID.
  • --output: Output file path.
4. get-atlas-entry — Get Full HPA Entry

Fetches the full metadata for a gene, including IHC scores, RNA-seq consensus, and subcellular location.

bash
uv run scripts/hpa_cli.py get-atlas-entry ENSG00000254647 \
  --output /tmp/ins_entry.json

Arguments:

  • ensembl_id (positional): The Ensembl Gene ID.
  • --format: Format of the returned entry, e.g., json (default: json).
  • --output: Output file path.
5. search-hpa — Search by Attribute

Allows filtering for genes based on specific criteria (e.g., "elevated in amygdala").

bash
uv run scripts/hpa_cli.py search-hpa \
  --query "brain_category_rna:amygdala" \
  --output /tmp/search_results.json

Arguments:

  • --query: The search query string. Refer to references/search-api.md for details.
  • --output: Output file path.

Core Rules

  • Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce fair use and implement retry logic.
  • Notification: If this skill is used, ensure this is mentioned in the output.

API Versioning

The HPA website at www.proteinatlas.org always serves the latest data release. Older archived versions can be accessed via vNN.proteinatlas.org (e.g., v24.proteinatlas.org), while the current version's subdomain redirects to www.proteinatlas.org. This skill's scripts query the latest version by default.

Common Errors

  • If no results are returned, confirm the query is detailed enough starting with the api reference in references/search-api.md
  • If you cannot find the results, search the web for example HPA queries and use these to construct a better query.
  • The output is usually large. Use jq or write your own python data parsing library to process the search results. Never output to stdout, or cat the output file.

© google-deepmind, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/human_protein_atlas_database of google-deepmind/science-skills.

  • SKILL.md
  • references/citation.bib
  • references/search-api.md
  • scripts/hpa_cli.py

Open the folder on GitHubat commit 6883275

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in google-deepmind/science-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Human Protein Atlas Database next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Annotating Variantsmaziyarpanahi/openmed5.5k—~2.1kAutomated safety check: PassApache-2.0
Ggetdavila7/claude-code-templates32k10 repos~6.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Human Protein Atlas Database

What does Human Protein Atlas Database do?

A skill your agent uses when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA). Human Protein Atlas Database is an agent skill from google-deepmind/science-skills. Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).

When should I use Human Protein Atlas Database?

Human Protein Atlas Database fits situations like: you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA); tasks that involve Internationalization.

How do I install Human Protein Atlas Database in Claude Code?

Run `npx skills add google-deepmind/science-skills --skill human-protein-atlas-database -a claude-code`. Or copy the skill folder (skills/human_protein_atlas_database in google-deepmind/science-skills) into .claude/skills/human-protein-atlas-database in your project. Claude Code loads it when a task matches its description.

How do I install Human Protein Atlas Database in Codex?

Run `npx skills add google-deepmind/science-skills --skill human-protein-atlas-database -a codex`. Or copy the skill folder (skills/human_protein_atlas_database in google-deepmind/science-skills) into .agents/skills/human-protein-atlas-database in your project. Codex loads it when a task matches its description.

Can I use Human Protein Atlas Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google-deepmind/science-skills --skill human-protein-atlas-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/human-protein-atlas-database, .gemini/skills/human-protein-atlas-database, .github/skills/human-protein-atlas-database and .opencode/skills/human-protein-atlas-database in your project.

What does Human Protein Atlas Database need to run?

Going by SKILL.md and its folder, Human Protein Atlas Database needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Human Protein Atlas Database access the network?

SKILL.md names 1 domain. As links in the text: proteinatlas.org. This is read from the text; nothing was executed.

Is Human Protein Atlas Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Human Protein Atlas Database use?

Human Protein Atlas Database is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Human Protein Atlas Database use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Human Protein Atlas Database?

Skills that share tags, products or a category with Human Protein Atlas Database: External API Change (GuyTeichman/RNAlysis, 139 stars), Ensembl Database (davila7/claude-code-templates, 32k stars), Bio DB Tools (DrugClaw/DrugClaw, 125 stars) and Annotating Variants (maziyarpanahi/openmed, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Human Protein Atlas Database?

google-deepmind (a GitHub organization) maintains it in google-deepmind/science-skills, which has 3,226 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on September 15, 2026.

Source: google-deepmind/science-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.