Bio DB Tools
DrugClaw/DrugClaw
Query public biology databases and APIs including UniProt, RCSB PDB, AlphaFold DB, ClinVar, dbSNP, gnomAD, Ensembl, GEO, InterPro, KEGG, OpenTargets, Reactome, and STRING.
Retrieve and analyze AlphaFold predicted structures for a protein.
Install Alphafold Database Fetch And Analyze
$ npx skills add google-deepmind/science-skills --skill alphafold-database-fetch-and-analyze -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google-deepmind/science-skills alphafold-database-fetch-and-analyze --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/alphafold_database_fetch_and_analyze .claude/skills/alphafold-database-fetch-and-analyze && 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 "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .claude/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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/alphafold_database_fetch_and_analyzeType 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 alphafold-database-fetch-and-analyze -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google-deepmind/science-skills alphafold-database-fetch-and-analyze --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/alphafold_database_fetch_and_analyze .agents/skills/alphafold-database-fetch-and-analyze && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .agents/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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 alphafold-database-fetch-and-analyze -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google-deepmind/science-skills alphafold-database-fetch-and-analyze --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/alphafold_database_fetch_and_analyze .cursor/skills/alphafold-database-fetch-and-analyze && 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 "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .cursor/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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/alphafold_database_fetch_and_analyze--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 alphafold-database-fetch-and-analyze -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google-deepmind/science-skills alphafold-database-fetch-and-analyze --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/alphafold_database_fetch_and_analyze .gemini/skills/alphafold-database-fetch-and-analyze && 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 "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .gemini/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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 alphafold-database-fetch-and-analyzeInstalls 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 alphafold-database-fetch-and-analyze -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/alphafold_database_fetch_and_analyze .github/skills/alphafold-database-fetch-and-analyze && 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 "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .github/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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 alphafold-database-fetch-and-analyze -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 alphafold-database-fetch-and-analyze --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/alphafold_database_fetch_and_analyze .opencode/skills/alphafold-database-fetch-and-analyze && 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 "alphafold-database-fetch-and-analyze" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/alphafold_database_fetch_and_analyze into .opencode/skills/alphafold-database-fetch-and-analyze/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold-database-fetch-and-analyze", 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.
Facts
- Skill name
alphafold-database-fetch-and-analyze- GitHub stars
- 3.2k
- Used in
- 2 other repos
- Token cost
- ~1.2k tokens
- SKILL.md length
- 551 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 40
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Retrieve and analyze AlphaFold predicted structures for a protein.
- Works in 2 steps: uv: Read the uv skill and follow its… → User Notification: If
- The user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT)
- SKILL.md covers Prerequisites, Overview, Core Rules and Utility Scripts, plus 1 more section
- Runs Python scripts from its folder; calls uv
What it does
Alphafold Database Fetch And Analyze is an agent skill from google-deepmind/science-skills. Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `scripts/analyze_pae.py`, `scripts/analyze_plddt.py` and `scripts/fetch_structure.py`).
It sits in Research & Science, covering Protein structure and design. It works with AlphaFold and UniProt. 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
- The user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT)
- Domain boundary analysis
- Disorder assessment
- The user only has a protein name
Example prompts
- “/alphafold-database-fetch-and-analyze”
Requirements
- Python 3
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- uv: Read the uv skill and follow its Setup instructions to ensure
- User Notification: If
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 3 files 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):
alphafold.ebi.ac.ukuniprot.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
Alphafold Database Fetch And Analyze loads about 1.2k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 93 tokens; SKILL.md has 551 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.
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). 551 words, ~1,189 tokens.
Download SKILL.mdSave it as
.claude/skills/alphafold-database-fetch-and-analyze/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- alphafold-database-fetch-and-analyze
- description
- Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
AlphaFold Database: Fetch and Analyze
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/alphafold_database_fetch_and_analyze_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://alphafold.ebi.ac.uk/, then (2) create the file recording the notification text and timestamp.
Overview
Downloads AlphaFold predicted structures (mmCIF) and Predicted Aligned Error (PAE) matrices from the AlphaFold Database for a given UniProt ID, then performs automated heuristic analysis on structural confidence (pLDDT), intrinsically disordered regions, rigid domain boundaries, and inter-domain flexibility.
Do NOT use when:
- The user only has a protein name, gene name, or amino acid sequence (no UniProt ID) — ask them to look up the ID on UniProt.
- The user wants to search for structural homologs (use Foldseek).
- The user wants to run AlphaFold predictions on a custom sequence.
- The user needs experimental PDB structures (use RCSB PDB).
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 the required rate limit gracefully.
- Do not attempt to calculate domain boundaries or assess structural disorder yourself; always rely on the output provided by the script.
- If this skill is used, ensure this is mentioned in the output.
Utility Scripts
1. Fetch Structure Files
Downloads the .cif structure file, _predicted_aligned_error.json, and API
metadata JSON (-metadata.json) for a UniProt ID. Handles fragment fallback for
very large proteins.
Examples:
uv run scripts/fetch_structure.py P00520 -o /path/to/output/
uv run scripts/fetch_structure.py P04637 -o /path/to/custom_results/Always specify -o with an absolute path or a path relative to the user's
project root, never a path relative to the skill directory.
2. Analyze pLDDT Confidence
Reads pLDDT confidence metrics from a saved AFDB metadata JSON file (produced by
fetch_structure.py) and prints a heuristic confidence assessment (structured,
disordered, mixed).
Example:
uv run scripts/analyze_plddt.py ./data/AF-P00520-F1-metadata.json3. Analyze PAE / Domain Boundaries
Reads a downloaded PAE JSON file and detects rigid domain boundaries using a sliding-window PAE heuristic.
Example:
uv run scripts/analyze_pae.py ./data/AF-P00520-F1-predicted_aligned_error_v6.jsonShow full SKILL.md (225 more words)Show less
Interpreting the Output
The script prints analysis to stdout. Read it carefully and synthesize the results for the user:
- Isoform / Large Protein Warning (MANDATORY): Check the script output for
any
[!] WARNINGlines. If the script reports that no canonical entry was found and an isoform was used, or if the protein is very large (>2700 AAs), you MUST prominently relay this warning to the user. Do not omit this warning. - Synthesize the Structural Analysis: Combine the "pLDDT Conclusion" and the "PAE Structural Conclusion" into a single, cohesive overall summary. Describe the protein's overall folding confidence, the presence of disordered regions, and its rigid domain layout.
- Highlight the supporting metrics:
- Overall Global pLDDT and the breakdown of fraction confidence (especially Very Low vs. Very High).
- Domain Boundary Analysis (number of distinct global domains and their specific residue ranges).
- Explicit Disorder Warning: If the analysis concludes that the protein is highly intrinsically disordered (e.g., high fraction of <50 pLDDT or lack of rigid domains), issue a separate, prominent warning. Advise the user against proceeding with whole-protein downstream structural analysis (like Foldseek or docking). If small ordered domains exist amidst the disorder, advise the user to restrict any future analysis strictly to those specific residue boundaries.
- Remind the user that per-residue pLDDT is embedded in the B-factor column of the downloaded mmCIF 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 4 other files (scripts, references) in skills/alphafold_database_fetch_and_analyze of google-deepmind/science-skills.
- SKILL.md
- references/citation.bib
- scripts/analyze_pae.py
- scripts/analyze_plddt.py
- scripts/fetch_structure.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
Alphafold Database Fetch And Analyze 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 |
|---|---|---|---|---|---|---|
| Alphafold Database Fetch And Analyze this skillgoogle-deepmind/science-skills | 3.2k | 2 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Bio DB ToolsDrugClaw/DrugClaw | 125 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Ggetdavila7/claude-code-templates | 32k | 10 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Alphafold Databasedavila7/claude-code-templates | 32k | 10 repos | ~4k | Automated safety check: Pass | MIT | |
| Tooluniverse Protein Structure Retrievalwu-yc/LabClaw | 1.1k | 2 repos | ~2.8k | Automated safety check: Pass | None | |
| Bio Structural Biology Alphafold PredictionsFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~2.1k | Automated safety check: Pass | None |
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Alphafold Database
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Access AlphaFold's 200M+ AI-predicted protein structures. An agent skill from davila7/claude-code-templates.
Tooluniverse Protein Structure Retrieval
wu-yc/LabClaw
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Bio Structural Biology Alphafold Predictions
FreedomIntelligence/OpenClaw-Medical-Skills
Access and analyze AlphaFold protein structure predictions. An agent skill from FreedomIntelligence/OpenClaw-Medical-Skills.
Alphafold DB
aipoch/medical-research-skills
Access over 200M protein structures from AlphaFold DB; use when you need to retrieve predicted 3D structures (PDB/mmCIF), confidence metrics (pLDDT/PAE), or protein metadata by UniProt accession.
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Related
Categories
Questions about Alphafold Database Fetch And Analyze
What does Alphafold Database Fetch And Analyze do?
Retrieve and analyze AlphaFold predicted structures for a protein. Alphafold Database Fetch And Analyze is an agent skill from google-deepmind/science-skills. Retrieve and analyze AlphaFold predicted structures for a protein.
When should I use Alphafold Database Fetch And Analyze?
Alphafold Database Fetch And Analyze fits situations like: the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT); domain boundary analysis; disorder assessment; the user only has a protein name.
How do I install Alphafold Database Fetch And Analyze in Claude Code?
Run `npx skills add google-deepmind/science-skills --skill alphafold-database-fetch-and-analyze -a claude-code`. Or copy the skill folder (skills/alphafold_database_fetch_and_analyze in google-deepmind/science-skills) into .claude/skills/alphafold-database-fetch-and-analyze in your project. Claude Code loads it when a task matches its description.
How do I install Alphafold Database Fetch And Analyze in Codex?
Run `npx skills add google-deepmind/science-skills --skill alphafold-database-fetch-and-analyze -a codex`. Or copy the skill folder (skills/alphafold_database_fetch_and_analyze in google-deepmind/science-skills) into .agents/skills/alphafold-database-fetch-and-analyze in your project. Codex loads it when a task matches its description.
Can I use Alphafold Database Fetch And Analyze 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 alphafold-database-fetch-and-analyze -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alphafold-database-fetch-and-analyze, .gemini/skills/alphafold-database-fetch-and-analyze, .github/skills/alphafold-database-fetch-and-analyze and .opencode/skills/alphafold-database-fetch-and-analyze in your project.
What does Alphafold Database Fetch And Analyze need to run?
Going by SKILL.md and its folder, Alphafold Database Fetch And Analyze needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Alphafold Database Fetch And Analyze access the network?
SKILL.md names 2 domains. As links in the text: alphafold.ebi.ac.uk and uniprot.org. This is read from the text; nothing was executed.
Is Alphafold Database Fetch And Analyze 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 Alphafold Database Fetch And Analyze use?
Alphafold Database Fetch And Analyze 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 Alphafold Database Fetch And Analyze use?
About 1.2k tokens (SKILL.md is roughly 4.8k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Alphafold Database Fetch And Analyze?
Skills that share tags, products or a category with Alphafold Database Fetch And Analyze: Bio DB Tools (DrugClaw/DrugClaw, 125 stars), Gget (davila7/claude-code-templates, 32k stars), Alphafold Database (davila7/claude-code-templates, 32k stars) and Tooluniverse Protein Structure Retrieval (wu-yc/LabClaw, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Alphafold Database Fetch And Analyze?
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.