GitHub Deep Research
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.
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al.
Install Alphafold2
$ npx skills add JimLiu/science-skills --skill alphafold2 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install JimLiu/science-skills alphafold2 --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/JimLiu/science-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/alphafold2 .claude/skills/alphafold2 && 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 "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .claude/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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/JimLiu/science-skills/tree/main/skills/alphafold2Type 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 JimLiu/science-skills --skill alphafold2 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install JimLiu/science-skills alphafold2 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/science-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/alphafold2 .agents/skills/alphafold2 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .agents/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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 JimLiu/science-skills --skill alphafold2 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install JimLiu/science-skills alphafold2 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/science-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/alphafold2 .cursor/skills/alphafold2 && 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 "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .cursor/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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/JimLiu/science-skills.git --path skills/alphafold2--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 JimLiu/science-skills --skill alphafold2 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install JimLiu/science-skills alphafold2 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/science-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/alphafold2 .gemini/skills/alphafold2 && 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 "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .gemini/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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 JimLiu/science-skills alphafold2Installs 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 JimLiu/science-skills --skill alphafold2 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/JimLiu/science-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/alphafold2 .github/skills/alphafold2 && 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 "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .github/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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 JimLiu/science-skills --skill alphafold2 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install JimLiu/science-skills alphafold2 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/science-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/alphafold2 .opencode/skills/alphafold2 && 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 "alphafold2" agent skill from https://github.com/JimLiu/science-skills/tree/main/skills/alphafold2 into .opencode/skills/alphafold2/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alphafold2", 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
alphafold2- GitHub stars
- 227
- Used in
- 4 other repos
- Token cost
- ~1.2k tokens
- SKILL.md length
- 486 words
- Files
- 1
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al.
- Tasks that involve Protein structure and design
- SKILL.md covers Running it, Unified-memory defaults loop…, The MSA server is the… and Errors worth recognizing
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Alphafold2 is an agent skill from JimLiu/science-skills. Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Protein structure and design. It works with GitHub. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Protein structure and design
Example prompts
- “/alphafold2”
What it can do on your machine
Read from SKILL.md and the folder at commit fb309c3. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
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
Alphafold2 loads about 1.2k tokens when it runs. Until then it costs about 106 tokens; SKILL.md has 486 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from JimLiu/science-skills at commit fb309c3, republished under its Apache-2.0 licence (© JimLiu). 486 words, ~1,235 tokens.
Download SKILL.mdSave it as
.claude/skills/alphafold2/SKILL.md (or your agent's skills folder).- name
- alphafold2
- description
- Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.
- license
- Apache-2.0
- category
- biomodels
- requirements
- gpu
- metadata.display-name
- AlphaFold2
AlphaFold2 (ColabFold runner)
This skill wraps AlphaFold2 and AlphaFold2-Multimer through colabfold_batch,
which replaces DeepMind's local-database MSA pipeline with a call to the public
MMseqs2 server — so a prediction is one command and one FASTA, not a 2 TB
database mount. AF2 remains the reference monomer predictor and the multimer
model is still a strong protein–protein validator, but it does not handle
ligands or nucleic acids; for those, route to boltz, chai1, or openfold3.
The ColabFold code is MIT (github.com/sokrypton/ColabFold) and the AlphaFold2
code is Apache-2.0 (github.com/google-deepmind/alphafold); the AF2 model
parameters are CC-BY-4.0 with DeepMind's terms of use.
Running it
colabfold_batch input.fasta out \
--num-recycle 3 \
--model-type alphafold2_multimer_v3The input is a plain FASTA. For a complex, put every chain on one sequence
line separated by : — colabfold_batch builds a paired MSA per segment and
runs the multimer model when it sees the colon (so the explicit --model-type alphafold2_multimer_v3 above is belt-and-braces). For monomers omit
--model-type and the colon. --templates and --amber add PDB templates
and OpenMM relaxation respectively; both are off by default and both add
minutes per model.
ColabFold runs all five AF2 model weights by default and ranks them by pLDDT
(pTM/ipTM for multimer), so output per query lands in out/ as five ranked
PDBs <name>_unrelaxed_rank_00{1..5}_*.pdb (b-factor column carries pLDDT)
and a matching <name>_scores_rank_00{N}_*.json with plddt, ptm, and — for
multimer — iptm and the pae matrix. Rank-1 is the model to read first;
ipTM > 0.5 is the usual soft pass for an interface.
Unified-memory defaults loop forever under gVisor — the env patches them out
colabfold/batch.py hard-sets TF_FORCE_UNIFIED_MEMORY=1 and
XLA_PYTHON_CLIENT_MEM_FRACTION=4.0 on import. Under a gVisor sandbox unified
memory is unsupported, so JAX's device_put loops indefinitely allocating
host RAM during AF2 parameter load — the job appears hung, never errors.
Override both before the import (TF_FORCE_UNIFIED_MEMORY=0, fraction
0.95), or sed-patch the two assignments out of batch.py in the image
build, or the first fold never starts.
Show full SKILL.md (181 more words)Show less
The MSA server is the wall-clock bottleneck, and it is shared
colabfold_batch defaults to --msa-mode mmseqs2_uniref_env, which posts your
sequence to api.colabfold.com. That server is a public, rate-limited
resource: the wait dominates short folds and occasionally times out under load.
For campaigns, run the MSA stage once with --msa-only, keep the resulting
.a3m files, and feed the directory back as the input on subsequent runs — the
GPU stage then starts immediately and the server is not hit again.
Errors worth recognizing
| You see | It means / do this |
|---|---|
| Job hangs silently during "Running model_1" with host RAM climbing | Unified-memory loop under gVisor — see the gotcha above; override or patch batch.py. |
RESOURCE_EXHAUSTED / OOM during XLA compile | XLA_PYTHON_CLIENT_MEM_FRACTION too high for the GPU — drop below the 0.95 default to 0.9 or so. |
MSA stage hangs at Submitting job | Public MMseqs2 server is rate-limiting — wait, or pre-compute with --msa-only and re-run from the cached .a3m. |
Next: for designed-sequence validation, superpose the rank-1 model onto
the design backbone with US-align and gate on pLDDT/ipTM thresholds; for
ligand-bearing complexes, hand the same chains to boltz or chai1.
© JimLiu, 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
Just SKILL.md in skills/alphafold2 of JimLiu/science-skills.
Open the folder on GitHubat commit fb309c3
Used in 4 other repositories
We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in JimLiu/science-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Alphafold2 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 |
|---|---|---|---|---|---|---|
| Alphafold2 this skillJimLiu/science-skills | 227 | 4 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | 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 | 163 | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Rival Search MCPdamionrashford/RivalSearchMCP | 132 | 1 repos | ~796 | Automated safety check: Pass | MIT | |
| Bindcraftadaptyvbio/protein-design-skills | 163 | 4 repos | ~1.3k | Automated safety check: Pass | MIT |
Similar skills
Alphafold Database Fetch And Analyze
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
Alphafold
adaptyvbio/protein-design-skills
Validate protein designs using AlphaFold2 structure prediction.
Rival Search MCP
damionrashford/RivalSearchMCP
Deterministic deep research via RivalSearchMCP. An agent skill from damionrashford/RivalSearchMCP.
Bindcraft
adaptyvbio/protein-design-skills
End-to-end binder design using BindCraft hallucination. An agent skill from adaptyvbio/protein-design-skills.
Read GitHub
AgentTeam-TaichuAI/ScienceClaw
Read and search GitHub repository documentation via gitmcp.io MCP service.
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Set up a compute environment on a remote provider so Claude Science jobs can run there.
Borzoi
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Openfold3
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Related
Works with
Categories
Questions about Alphafold2
What does Alphafold2 do?
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. Alphafold2 is an agent skill from JimLiu/science-skills. Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al.
When should I use Alphafold2?
Alphafold2 fits situations like: tasks that involve Protein structure and design.
How do I install Alphafold2 in Claude Code?
Run `npx skills add JimLiu/science-skills --skill alphafold2 -a claude-code`. Or copy the skill folder (skills/alphafold2 in JimLiu/science-skills) into .claude/skills/alphafold2 in your project. Claude Code loads it when a task matches its description.
How do I install Alphafold2 in Codex?
Run `npx skills add JimLiu/science-skills --skill alphafold2 -a codex`. Or copy the skill folder (skills/alphafold2 in JimLiu/science-skills) into .agents/skills/alphafold2 in your project. Codex loads it when a task matches its description.
Can I use Alphafold2 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 JimLiu/science-skills --skill alphafold2 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alphafold2, .gemini/skills/alphafold2, .github/skills/alphafold2 and .opencode/skills/alphafold2 in your project.
What does Alphafold2 need to run?
SKILL.md names no scripts, command-line tools or credentials: Alphafold2 is instructions for the agent only.
Does Alphafold2 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 Alphafold2 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. Review the folder before installing.
What licence does Alphafold2 use?
Alphafold2 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 Alphafold2 use?
About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Alphafold2?
Skills that share tags, products or a category with Alphafold2: GitHub Deep Research (bytedance/deer-flow, 83k stars), Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars), Alphafold (adaptyvbio/protein-design-skills, 163 stars) and Rival Search MCP (damionrashford/RivalSearchMCP, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Alphafold2?
JimLiu (a GitHub user) maintains it in JimLiu/science-skills, which has 227 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on July 1, 2026.
Source: JimLiu/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.