External API Change
GuyTeichman/RNAlysis
Workflow for fixing or changing RNAlysis code that talks to an EXTERNAL WEB SERVICE — UniProt, Ensembl, PANTHER, PhylomeDB, OrthoInspector, KEGG, or GO.
Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP).
$ npx skills add google-deepmind/science-skills --skill ensembl-database -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google-deepmind/science-skills ensembl-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/ensembl_database .claude/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .claude/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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/ensembl_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 ensembl-database -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google-deepmind/science-skills ensembl-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/ensembl_database .agents/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .agents/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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 ensembl-database -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google-deepmind/science-skills ensembl-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/ensembl_database .cursor/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .cursor/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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/ensembl_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 ensembl-database -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google-deepmind/science-skills ensembl-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/ensembl_database .gemini/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .gemini/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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 ensembl-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 ensembl-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/ensembl_database .github/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .github/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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 ensembl-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 ensembl-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/ensembl_database .opencode/skills/ensembl-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 "ensembl-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ensembl_database into .opencode/skills/ensembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ensembl-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.
ensembl-databaseQuery the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP).
Ensembl Database is an agent skill from google-deepmind/science-skills. Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.
Its SKILL.md is about 2.2k 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/ensembl_rest_api_reference.md` and `scripts/ensembl_api.py`).
It sits in Research & Science, covering Bioinformatics and Translation. 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.
2 steps, taken from the first numbered list 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):
useast.ensembl.orggithub.comFrom 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.
Ensembl Database loads about 2.2k tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 824 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). 824 words, ~2,202 tokens.
.claude/skills/ensembl-database/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.The Ensembl database is a resource for genome annotation. This skill allows you to interact with the Ensembl REST API to resolve ambiguous symbols, cross-reference IDs (RefSeq, HGNC, UniProt, ENSG), fetch raw sequences, and retrieve detailed transcript structures.
Key Concepts:
"human". You MUST explicitly flag this default to the user to
ensure they are aware.--assembly GRCh37 flag. You MUST explicitly flag to the
user when a non-default assembly is being used./tmp by default, or to a user-specified file using the --output
flag. It also prints a concise summary to stdout.1. Resolve Gene ID — Resolve a symbol, alias, or RefSeq ID to ENSG ID(s). Automatically falls back to resolving synonyms if primary symbol is not found.
uv run scripts/ensembl_api.py resolve-gene TP53 --species human --output tp53.json
uv run scripts/ensembl_api.py resolve-gene PCL2 --output pcl2.json # Falls back to synonym resolution2. Map ID to External Database — Cross-reference an Ensembl ID to UniProt, HGNC, RefSeq, etc.
uv run scripts/ensembl_api.py map-id ENSG00000141510 --external-db UniProt --output uniprot_map.json
uv run scripts/ensembl_api.py map-id ENST00000269305 --external-db RefSeq_mRNA --output refseq_map.json3. Get Genomic Sequence — Fetch raw DNA for a coordinate window. Supports
GRCh37 via --assembly GRCh37.
uv run scripts/ensembl_api.py get-sequence 17:7661779-7687550 --species human --output seq.txt
uv run scripts/ensembl_api.py get-sequence chr9:21971100-21971200 --assembly GRCh37 --output seq_grch37.txt4. Gene Summary — High-level metadata: symbol, biotype, description, chromosomal location.
uv run scripts/ensembl_api.py gene-summary ENSG00000141510 --output gene_summary.json5. List Transcripts — All transcripts for a gene, with optional
--only-mane or --only-canonical filters. Output includes Transcript Support
Level (TSL).
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-mane --output transcripts_mane.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-canonical --output transcripts_canonical.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --output transcripts_all.json5b. Canonical TSS — Get the single coordinate of the Transcription Start Site (TSS) for the canonical transcript of a gene.
[!NOTE] Unlike the standard
transcriptscommand,canonical-tssaccepts both symbols (e.g.,TP53) and Ensembl IDs, and automatically resolves them. It also does the math for strand orientation (TSS isStartfor+strand andEndfor-strand), outputting the single integer coordinate directly.
uv run scripts/ensembl_api.py canonical-tss TP53 --output tp53_tss.json
uv run scripts/ensembl_api.py canonical-tss ENSG00000141510 --output tss.json6. Transcript Structure — Exon coordinates, CDS boundaries, and computed 5'/3' UTR regions for a transcript.
uv run scripts/ensembl_api.py transcript-structure ENST00000269305 --output structure.json7. Protein Info — ENSP ID and sequence length for a transcript.
uv run scripts/ensembl_api.py protein-info ENST00000269305 --output protein_info.json8. Protein Sequence — Amino acid FASTA for a transcript (ENST) or protein (ENSP) ID.
uv run scripts/ensembl_api.py protein-sequence ENST00000269305 --output protein.fasta
uv run scripts/ensembl_api.py protein-sequence ENSP00000269305 --output protein_ensp.fasta9. Variant Consequence (VEP) — Predict molecular consequences for a genomic variant. Includes open-licensed plugins: AlphaMissense, Conservation, DosageSensitivity, IntAct, MaveDB, OpenTargets, LoF (Loftee), NMD, UTRAnnotator, mutfunc, LOEUF.
uv run scripts/ensembl_api.py vep 9:21971147:T:C --species human --output vep.json
uv run scripts/ensembl_api.py vep rs699 --species human --output vep_rs699.jsonExample VEP stdout output:
[*] Variant: 9:21971147:T>C
[*] Most severe consequence: missense_variant
[*] Found 15 transcript consequences.
[*] VEP Predictions:
- ENST00000304494 (CDKN2A): Consequence = missense_variant
- ENST00000304494 (CDKN2A): Amino Acids = N/S
- ENST00000304494 (CDKN2A): SIFT = deleterious (0.01)
- ENST00000304494 (CDKN2A): AlphaMissense Class = likely_benign
- ENST00000304494 (CDKN2A): AlphaMissense Pathogenicity = 0.2129
- ENST00000304494 (CDKN2A): Conservation = 2.05
- ENST00000304494 (CDKN2A): Dosage Sensitivity (Haplo) = 0.889228328567991
- ENST00000304494 (CDKN2A): Dosage Sensitivity (Triplo) = 0.135514349094646
- ENST00000304494 (CDKN2A): Loss of Function (LOEUF) = 0.791Presenting VEP Results: After running the VEP command, you MUST present the full VEP Predictions list from stdout to the user. This list contains both standard VEP predictions (Consequence, Amino Acids, SIFT, PolyPhen) and open-license plugin results (AlphaMissense, Conservation, Dosage Sensitivity, LOEUF, Loftee LoF, NMD, UTRAnnotator, Mutfunc). Do NOT just summarize — show the complete list so the user can see all predictions. If the list is very long (many transcripts), show the MANE Select / canonical transcript rows in full and note that the complete data is in the JSON output.
If the user needs detailed, nested structural data (like the precise integer coordinates of Exon 2 of a transcript) that isn't summarized in stdout:
--output or the temporary file
path printed by the script).jq or write a quick, disposable python snippet to
extract the specific data point requested. Do not attempt to read the
entire JSON file into your context if it is very large.If you need to make an API call that the script does not support (e.g., fetching
protein domain annotations, coordinate mapping between assemblies, homology
searches, linkage disequilibrium, or phenotype lookups), read
references/ensembl_rest_api_reference.md for a complete reference of available
endpoints, parameters, and response fields.
CRITICAL: When writing custom scripts or using alternatives to the provided
scripts, you MUST respect the Ensembl REST API rate limits (maximum 15
requests per second) and handle 429 Too Many Requests errors gracefully (e.g.,
with exponential backoff).
© 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 3 other files (scripts, references) in skills/ensembl_database of google-deepmind/science-skills.
Open the folder on GitHubat commit 6883275
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in google-deepmind/science-skills, which our catalogue first saw on October 7, 2026.
Ensembl 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 |
|---|---|---|---|---|---|---|
| Ensembl Database this skillgoogle-deepmind/science-skills | 3.2k | 1 repos | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| External API ChangeGuyTeichman/RNAlysis | 140 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Ensembl Databasedavila7/claude-code-templates | 32k | 10 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Annotating Variantsmaziyarpanahi/openmed | 5.5k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Ggetdavila7/claude-code-templates | 32k | 11 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Scientific Pkg Ggetaffaan-m/ECC | 274k | 1 repos | ~1.3k | Automated safety check: Pass | MIT |
GuyTeichman/RNAlysis
Workflow for fixing or changing RNAlysis code that talks to an EXTERNAL WEB SERVICE — UniProt, Ensembl, PANTHER, PhylomeDB, OrthoInspector, KEGG, or GO.
davila7/claude-code-templates
Query Ensembl genome database REST API for 250+ species. An agent skill from davila7/claude-code-templates.
maziyarpanahi/openmed
Annotates VCF variants and normalizes HGVS nomenclature with public, license-free annotators (Ensembl VEP REST, VEP/SnpEff/ANNOVAR offline) and links variants to gnomAD population frequencies and…
davila7/claude-code-templates
CLI/Python toolkit for rapid bioinformatics queries. An agent skill from davila7/claude-code-templates.
affaan-m/ECC
gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
TianGzlab/OmicsClaw
Load when converting gene identifiers between Ensembl, Entrez, and HGNC symbol in a bulk RNA-seq count matrix.
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.
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 needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…
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.
Works with
Categories
Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Ensembl Database is an agent skill from google-deepmind/science-skills. Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP).
Ensembl Database fits situations like: tasks that involve Bioinformatics; tasks that involve Translation.
Run `npx skills add google-deepmind/science-skills --skill ensembl-database -a claude-code`. Or copy the skill folder (skills/ensembl_database in google-deepmind/science-skills) into .claude/skills/ensembl-database in your project. Claude Code loads it when a task matches its description.
Run `npx skills add google-deepmind/science-skills --skill ensembl-database -a codex`. Or copy the skill folder (skills/ensembl_database in google-deepmind/science-skills) into .agents/skills/ensembl-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 ensembl-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/ensembl-database, .gemini/skills/ensembl-database, .github/skills/ensembl-database and .opencode/skills/ensembl-database in your project.
Going by SKILL.md and its folder, Ensembl 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 2 domains. As links in the text: useast.ensembl.org and github.com. 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.
Ensembl 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 2.2k tokens (SKILL.md is roughly 8.8k 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 3.8k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Ensembl Database: External API Change (GuyTeichman/RNAlysis, 140 stars), Ensembl Database (davila7/claude-code-templates, 32k stars), Annotating Variants (maziyarpanahi/openmed, 5.5k stars) and Gget (davila7/claude-code-templates, 32k 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 3,216 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.