Gget
davila7/claude-code-templates
CLI/Python toolkit for rapid bioinformatics queries. An agent skill from davila7/claude-code-templates.
A skill your agent uses for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection.
Install Alphafold3
$ npx skills add VectorSpaceLab/AREX-Skill --skill alphafold3 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill alphafold3 --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/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .claude/skills/alphafold3 && 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 "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .claude/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3Type 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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill alphafold3 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .agents/skills/alphafold3 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .agents/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill alphafold3 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .cursor/skills/alphafold3 && 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 "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .cursor/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/alphafold3--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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill alphafold3 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .gemini/skills/alphafold3 && 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 "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .gemini/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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 VectorSpaceLab/AREX-Skill alphafold3Installs 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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .github/skills/alphafold3 && 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 "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .github/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill alphafold3 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/alphafold3 .opencode/skills/alphafold3 && 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 "alphafold3" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/alphafold3 into .opencode/skills/alphafold3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold3", 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
alphafold3- GitHub stars
- 330
- Token cost
- ~1.2k tokens
- SKILL.md length
- 444 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 159
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A skill your agent uses for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection.
- AlphaFold 3 input preparation
- SKILL.md covers Quick Route, First Checks, Common Task Routing and Repository Facts, plus 2 more sections
- Runs Python scripts from its folder; calls python
- Prediction command planning
What it does
Alphafold3 is an agent skill from VectorSpaceLab/AREX-Skill. Use this skill for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection. Covers the local AlphaFold 3 inference package, its JSON dialect, runalphafold workflow, outputs, troubleshooting, and safe helper scripts.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/capability-map.md`, `references/repo-provenance.md` and `references/repo-routing-metadata.json`).
It sits in Research & Science, covering Protein structure and design. It works with AlphaFold and Python. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.
When your agent uses it
- AlphaFold 3 input preparation
- Prediction command planning
- Output interpretation
- Python API inspection
Example prompts
- “/alphafold3”
Requirements
- Python 3
- Docker
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. 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:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Alphafold3 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 70 tokens; SKILL.md has 444 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 VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 444 words, ~1,197 tokens.
Download SKILL.mdSave it as
.claude/skills/alphafold3/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- alphafold3
- description
- Use this skill for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection. Covers the local AlphaFold 3 inference package, its JSON dialect, run_alphafold workflow, outputs, troubleshooting, and safe helper scripts.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- Apache 2.0
AlphaFold 3
Use this repo skill when a user asks an agent to work with AlphaFold 3 inference workflows: preparing fold-input JSON, planning or debugging prediction runs, interpreting output directories, or writing safe Python tooling around the package.
AlphaFold 3 full prediction is operationally heavy. It requires Linux, model parameters obtained under the AlphaFold 3 terms, genetic databases, HMMER tools, compatible JAX/CUDA runtime, and an NVIDIA GPU for inference. Do not run full inference, download databases, mount disks, or fetch model weights unless the user explicitly asks and the environment is ready.
Quick Route
- Use
sub-skills/input-preparation/when constructing, validating, converting, or troubleshooting AlphaFold 3 input JSON. - Use
sub-skills/running-predictions/when planning Docker/local commands, split data-pipeline/inference runs, database/model paths, GPU flags, HMMER tools, or runtime preflight checks. - Use
sub-skills/output-interpretation/when inspecting result directories, ranking predictions, explaining confidence JSONs, embeddings, distograms, compression, or missing output files. - Use
sub-skills/python-apis/when coding against AlphaFold 3 internals such asfolding_input.Input,DataPipelineConfig,make_model_config,process_fold_input,ModelRunner, or structure/mmCIF utilities.
First Checks
For a local Python installation, start with a safe import/resource check rather than a prediction run:
python scripts/check_install.pyIf the package imports fail, read references/troubleshooting.md. If the input JSON is the suspected problem, use sub-skills/input-preparation/scripts/validate_fold_input.py. If runtime paths or binaries are suspected, use sub-skills/running-predictions/scripts/check_runtime_requirements.py.
Common Task Routing
| User asks for | Read first | Useful bundled helper |
|---|---|---|
| “Create an AF3 JSON for a protein-ligand complex” | sub-skills/input-preparation/SKILL.md | sub-skills/input-preparation/scripts/validate_fold_input.py |
| “Convert/check AlphaFold Server JSON” | sub-skills/input-preparation/references/input-json.md | sub-skills/input-preparation/scripts/validate_fold_input.py |
| “Run only the data pipeline on CPU” | sub-skills/running-predictions/SKILL.md | sub-skills/running-predictions/scripts/build_run_command.py |
| “Debug missing HMMER/database/model paths” | sub-skills/running-predictions/references/troubleshooting.md | sub-skills/running-predictions/scripts/check_runtime_requirements.py |
| “Explain ranking_scores.csv or ipTM/pLDDT/PAE” | sub-skills/output-interpretation/SKILL.md | sub-skills/output-interpretation/scripts/summarize_outputs.py |
| “Use AlphaFold3 APIs in Python” | sub-skills/python-apis/SKILL.md | sub-skills/python-apis/scripts/inspect_alphafold3_api.py |
Show full SKILL.md (184 more words)Show less
Repository Facts
- Distribution/import name:
alphafold3. - Verified version for this skill baseline:
3.0.3. - Python requirement from package metadata: Python
>=3.12. - Main runner:
run_alphafold.pyin source distributions or containers. - Console entry point:
build_data, used to generate internal CCD pickle resources from packagedcomponents.cifdata when needed. - Package dependencies include JAX, Haiku, RDKit, Tokamax, NumPy, zstandard, and compiled pybind extensions.
Safety Boundaries
- Do not download full genetic databases automatically; documented full database setup is hundreds of GB.
- Do not assume model parameters are present or licensed; they must be obtained directly from Google DeepMind under the model parameter terms.
- Do not run GPU inference as a smoke test unless the user requests it and supplies weights, databases or precomputed features, and output space.
- Treat
fetch_databases.sh, SSD mount/copy helpers, Docker build, and fullrun_alphafold.pyruns as user-approved operational actions, not default validation. - Prefer command generation, import checks, JSON validation, and output-tree inspection for safe agent assistance.
References
- Read
references/capability-map.mdfor the coverage map and ownership boundaries. - Read
references/troubleshooting.mdfor cross-cutting install/import/resource/runtime problems. - Read
references/repo-provenance.mdto decide whether this skill may be stale against a changed AlphaFold 3 checkout.
© VectorSpaceLab, 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 6 other files (scripts, references) in skills/repositories/repo-skills/alphafold3 of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/capability-map.md
- references/repo-provenance.md
- references/repo-routing-metadata.json
- references/troubleshooting.md
- scripts/check_install.py
- sub-skills
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Alphafold3 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 |
|---|---|---|---|---|---|---|
| Alphafold3 this skillVectorSpaceLab/AREX-Skill | 330 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Ggetdavila7/claude-code-templates | 32k | 10 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Chai1JimLiu/science-skills | 227 | 4 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Ggetaipoch/medical-research-skills | 2k | — | ~816 | Automated safety check: Pass | MIT | |
| Alphafold Database Fetch And Analyzegoogle-deepmind/science-skills | 3.2k | 2 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Alphafoldadaptyvbio/protein-design-skills | 164 | 3 repos | ~1.2k | Automated safety check: Pass | MIT |
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Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab).
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aipoch/medical-research-skills
Unified CLI/Python interface for querying genomic, proteomic, structure, and expression data across 20+ bioinformatics databases; use when you need fast, scriptable retrieval by gene/protein IDs or…
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Retrieve and analyze AlphaFold predicted structures for a protein.
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Validate protein designs using AlphaFold2 structure prediction.
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Categories
Questions about Alphafold3
What does Alphafold3 do?
A skill your agent uses for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection. Alphafold3 is an agent skill from VectorSpaceLab/AREX-Skill. Use this skill for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection.
When should I use Alphafold3?
Alphafold3 fits situations like: alphaFold 3 input preparation; prediction command planning; output interpretation; Python API inspection.
How do I install Alphafold3 in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill alphafold3 -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/alphafold3 in VectorSpaceLab/AREX-Skill) into .claude/skills/alphafold3 in your project. Claude Code loads it when a task matches its description.
How do I install Alphafold3 in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill alphafold3 -a codex`. Or copy the skill folder (skills/repositories/repo-skills/alphafold3 in VectorSpaceLab/AREX-Skill) into .agents/skills/alphafold3 in your project. Codex loads it when a task matches its description.
Can I use Alphafold3 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 VectorSpaceLab/AREX-Skill --skill alphafold3 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alphafold3, .gemini/skills/alphafold3, .github/skills/alphafold3 and .opencode/skills/alphafold3 in your project.
What does Alphafold3 need to run?
Going by SKILL.md and its folder, Alphafold3 needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; Docker.
Does Alphafold3 access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Alphafold3 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 Alphafold3 use?
Alphafold3 is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Alphafold3 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 Alphafold3?
Skills that share tags, products or a category with Alphafold3: Gget (davila7/claude-code-templates, 32k stars), Chai1 (JimLiu/science-skills, 227 stars), Gget (aipoch/medical-research-skills, 2k stars) and Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Alphafold3?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 330 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.