Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
A skill your agent uses when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
$ npx skills add google-deepmind/science-skills --skill gtex-database -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google-deepmind/science-skills gtex-database --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gtex_database .claude/skills/gtex-database && rm -rf skills-srcUse ~/.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/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .claude/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_databaseType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google-deepmind/science-skills --skill gtex-database -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google-deepmind/science-skills gtex-database --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/gtex_database .agents/skills/gtex-database && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .agents/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill gtex-database -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google-deepmind/science-skills gtex-database --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/gtex_database .cursor/skills/gtex-database && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .cursor/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google-deepmind/science-skills.git --path skills/gtex_database--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google-deepmind/science-skills --skill gtex-database -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google-deepmind/science-skills gtex-database --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/gtex_database .gemini/skills/gtex-database && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .gemini/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google-deepmind/science-skills gtex-databaseInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google-deepmind/science-skills --skill gtex-database -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/gtex_database .github/skills/gtex-database && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .github/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill gtex-database -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google-deepmind/science-skills gtex-database --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/gtex_database .opencode/skills/gtex-database && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "gtex-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/gtex_database into .opencode/skills/gtex-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gtex-database", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
gtex-databaseA skill your agent uses when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
Gtex Database is an agent skill from google-deepmind/science-skills. Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files (for example `scripts/gtex_cli.py`).
It sits in Research & Science. 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.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 6883275. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
gtexportal.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Gtex Database loads about 1.5k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 607 words of instructions outside code blocks.
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.
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.
The full file from google-deepmind/science-skills at commit 6883275, republished under its Apache-2.0 licence (© google-deepmind). 607 words, ~1,515 tokens.
.claude/skills/gtex-database/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.This skill retrieves transcriptomics data (RNA expression baselines) and expression Quantitative Trait Loci (eQTLs) from the GTEx Portal API V2. It provides access to median TPM (Transcripts Per Million) values for genes and significant eQTLs for variants across 54 human tissue sites.
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.Use this skill when you need to:
Do NOT use when you need to:
CRITICAL: You MUST respect GTEx Portal API Terms of Use.
Pick the right command on the first try. Match the user's input to the correct subcommand below.
resolve-gencode-idget-median-expressionget-top-expressed-tissuesget-gene-eqtlsget-eqtls-in-region# Map the TNF gene symbol to its GENCODE ID
uv run scripts/gtex_cli.py resolve-gencode-id TNF --output /tmp/tnf_id.json
# Get median expression of a gene by GENCODE ID
uv run scripts/gtex_cli.py get-median-expression ENSG00000232810.2 --output /tmp/tnf_expr.jsonAll subcommands write JSON to disk. Always save output in the /tmp/ directory.
The default output file is /tmp/gtex_output.json if --output is not
specified.
resolve-gencode-id — Gene Symbol → GENCODE IDMaps a standard gene symbol (e.g., "JUN", "TNF") to its Versioned GENCODE ID. This ID is required for all other expression and eQTL calls.
uv run scripts/gtex_cli.py resolve-gencode-id TNF --output /tmp/tnf_id.jsonArguments:
gene_symbol (positional): The standard gene symbol (e.g., "TNF").--output: Output file path (default: /tmp/gtex_output.json).get-median-expression — Get Median Expression (TPM)Retrieves the median TPM for a gene across all 54 GTEx tissue sites or specified tissues.
uv run scripts/gtex_cli.py get-median-expression ENSG00000232810.2 \
--tissues "Whole Blood,Spleen" --output /tmp/expr.jsonArguments:
gencode_id (positional): The Versioned GENCODE ID.--tissues: Comma-separated list of tissue IDs (optional, defaults to all
54 tissues).--output: Output file path (default: /tmp/gtex_output.json).get-top-expressed-tissues — Get Top Expressed TissuesReturns the n tissues with the highest median expression for the target gene.
uv run scripts/gtex_cli.py get-top-expressed-tissues ENSG00000232810.2 \
--n 5 --output /tmp/top_tissues.jsonArguments:
gencode_id (positional): The Versioned GENCODE ID.--n: Number of top tissues to return (default: 5).--output: Output file path.get-gene-eqtls — Get All eQTLs for a GeneReturns every significant eQTL associated with the gene across specified tissues.
uv run scripts/gtex_cli.py get-gene-eqtls ENSG00000232810.2 \
--tissues "Whole Blood" --output /tmp/eqtls.jsonArguments:
gencode_id (positional): The Versioned GENCODE ID.--tissues: Comma-separated list of tissue IDs (optional, defaults to all).--output: Output file path.get-eqtls-in-region — Get eQTLs in Chromosomal RegionReturns all significant single-tissue eQTLs within a chromosomal window (up to 8Mb).
uv run scripts/gtex_cli.py get-eqtls-in-region chr17 7000000 7100000 "Esophagus - Muscularis" \
--output /tmp/region_eqtls.jsonArguments:
chromosome (positional): Chromosome name (e.g., chr17).start (positional): Start position.end (positional): End position (max 8Mb from start).tissue_id (positional): The target tissue ID.--output: Output file path.# Step 1: Map symbol to GENCODE ID
uv run scripts/gtex_cli.py resolve-gencode-id GATA4 --output /tmp/gata4_id.json
# Step 2: Query for top tissues using the resolved ID
uv run scripts/gtex_cli.py get-top-expressed-tissues <gencode_id> --n 5 \
--output /tmp/gata4_top.json© 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
SKILL.md and 2 other files (scripts, references) in skills/gtex_database of google-deepmind/science-skills.
Open the folder on GitHubat commit 6883275
We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in google-deepmind/science-skills, which our catalogue first saw on October 7, 2026.
Gtex 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Gtex Database this skillgoogle-deepmind/science-skills | 3.2k | 3 repos | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Hypothesis Generationspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 46k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Read arXiv Paperkarpathy/nanochat | 58k | 2 repos | ~494 | Automated safety check: Pass | MIT | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT |
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Yuan1z0825/nature-skills
Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.
karpathy/nanochat
Fetches the TeX source of an arXiv paper from its URL, reads it and writes a markdown summary tied to the nanochat project.
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
google-deepmind/science-skills
Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
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).
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
google-deepmind/science-skills
Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures.
Categories
A skill your agent uses when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites. Gtex Database is an agent skill from google-deepmind/science-skills. Use when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
Gtex Database fits situations like: research & Science work in your project.
Run `npx skills add google-deepmind/science-skills --skill gtex-database -a claude-code`. Or copy the skill folder (skills/gtex_database in google-deepmind/science-skills) into .claude/skills/gtex-database in your project. Claude Code loads it when a task matches its description.
Run `npx skills add google-deepmind/science-skills --skill gtex-database -a codex`. Or copy the skill folder (skills/gtex_database in google-deepmind/science-skills) into .agents/skills/gtex-database in your project. Codex loads it when a task matches its description.
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 gtex-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/gtex-database, .gemini/skills/gtex-database, .github/skills/gtex-database and .opencode/skills/gtex-database in your project.
Going by SKILL.md and its folder, Gtex Database needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.
SKILL.md names 1 domain. As links in the text: gtexportal.org. This is read from the text; nothing was executed.
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.
Gtex 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.
About 1.5k tokens (SKILL.md is roughly 6.1k 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 1.5k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Gtex Database: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
google-deepmind (a GitHub organization) maintains it in google-deepmind/science-skills, which has 3,220 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.