Alphafold Database Fetch And Analyze
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
Guidance for cell-free protein synthesis (CFPS) optimization.
Install Cell Free Expression
$ npx skills add adaptyvbio/protein-design-skills --skill cell-free-expression -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install adaptyvbio/protein-design-skills cell-free-expression --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/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cell-free-expression .claude/skills/cell-free-expression && 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 "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .claude/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expressionType 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 adaptyvbio/protein-design-skills --skill cell-free-expression -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install adaptyvbio/protein-design-skills cell-free-expression --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/cell-free-expression .agents/skills/cell-free-expression && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .agents/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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 adaptyvbio/protein-design-skills --skill cell-free-expression -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install adaptyvbio/protein-design-skills cell-free-expression --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/cell-free-expression .cursor/skills/cell-free-expression && 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 "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .cursor/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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/adaptyvbio/protein-design-skills.git --path skills/cell-free-expression--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 adaptyvbio/protein-design-skills --skill cell-free-expression -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install adaptyvbio/protein-design-skills cell-free-expression --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/cell-free-expression .gemini/skills/cell-free-expression && 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 "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .gemini/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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 adaptyvbio/protein-design-skills cell-free-expressionInstalls 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 adaptyvbio/protein-design-skills --skill cell-free-expression -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/cell-free-expression .github/skills/cell-free-expression && 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 "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .github/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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 adaptyvbio/protein-design-skills --skill cell-free-expression -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install adaptyvbio/protein-design-skills cell-free-expression --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/cell-free-expression .opencode/skills/cell-free-expression && 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 "cell-free-expression" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/cell-free-expression into .opencode/skills/cell-free-expression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cell-free-expression", 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
cell-free-expression- GitHub stars
- 163
- Used in
- 3 other repos
- Token cost
- ~2.8k tokens
- SKILL.md length
- 1,015 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
Guidance for cell-free protein synthesis (CFPS) optimization.
- Works in 6 steps: First 30 codons: Most critical - use… → Rare codon clusters: Avoid 2+ rare… → Rare codon content: Keep overall <5% of… → …
- Planning CFPS experiments
- SKILL.md covers System Selection Guide, CFPS Troubleshooting Matrix, Codon Optimization for CFPS and mRNA Template Design, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Cell Free Expression is an agent skill from adaptyvbio/protein-design-skills. Guidance for cell-free protein synthesis (CFPS) optimization. Use when: (1) Planning CFPS experiments, (2) Troubleshooting low yield or aggregation, (3) Optimizing DNA template design for CFPS, (4) Expressing difficult proteins (disulfide-rich, toxic, membrane).
Its SKILL.md is about 2.8k 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. The repository describes itself as: Claude Code skills for protein design. The licence is MIT.
When your agent uses it
- Planning CFPS experiments
- Troubleshooting low yield
- Optimizing DNA template design for CFPS
- Expressing difficult proteins (disulfide-rich
Example prompts
- “/cell-free-expression”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- First 30 codons: Most critical - use only high-frequency codons
- Rare codon clusters: Avoid 2+ rare codons within 10 nt
- Rare codon content: Keep overall <5% of coding sequence
- GC content: Target 40-60% for balanced expression
- Avoid runs: No >6 consecutive G or C residues (secondary structure)
- Strategic slow codons: Place rare codons between domains (aids folding!)
What it can do on your machine
Read from SKILL.md and the folder at commit 59dd633. 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.
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):
pmc.ncbi.nlm.nih.govnature.comncbi.nlm.nih.govmdpi.comjournals.plos.orgfebs.onlinelibrary.wiley.compnas.orgfrontiersin.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
Cell Free Expression loads about 2.8k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 1,015 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 adaptyvbio/protein-design-skills at commit 59dd633, republished under its MIT licence (© adaptyvbio). 1,015 words, ~2,790 tokens.
Download SKILL.mdSave it as
.claude/skills/cell-free-expression/SKILL.md (or your agent's skills folder).- name
- cell-free-expression
- description
- Guidance for cell-free protein synthesis (CFPS) optimization. Use when: (1) Planning CFPS experiments, (2) Troubleshooting low yield or aggregation, (3) Optimizing DNA template design for CFPS, (4) Expressing difficult proteins (disulfide-rich, toxic, membrane).
- license
- MIT
- category
- experimental
- tags
- expression, cfps, validation
Cell-Free Protein Synthesis (CFPS)
System Selection Guide
| System | Best For | Yield | PTMs | Disulfides | Cost |
|---|---|---|---|---|---|
| E. coli extract | Rapid prototyping, prokaryotic proteins | High (100-400 μg/mL) | None | Poor (reducing) | Low |
| E. coli PURE | Defined conditions, unnatural AAs | Medium (50-150 μg/mL) | None | Controllable | High |
| Wheat germ | Eukaryotic proteins, membrane proteins | High (100-500 μg/mL) | Limited | Moderate | Medium |
| Rabbit reticulocyte | Mammalian proteins, post-translational studies | Low (10-50 μg/mL) | Some | Poor | High |
| Insect (Sf21) | Glycoproteins, complex folds | Medium (50-100 μg/mL) | Glycosylation | Good | High |
| HeLa/CHO | Native mammalian proteins | Low (10-50 μg/mL) | Full mammalian | Good | Very High |
CFPS Troubleshooting Matrix
| Problem | Likely Causes | Design Fix | Reagent Fix |
|---|---|---|---|
| No expression | Rare codons at N-terminus, poor RBS | Codon optimize first 30 codons | Use BL21-CodonPlus extract |
| Low yield | Strong mRNA secondary structure, template issues | Optimize 5' UTR (ΔG > -5 kcal/mol) | Increase Mg²⁺ (10-18 mM), ATP |
| Aggregation | Hydrophobic protein, fast translation | Add solubility tags (MBP, SUMO) | Add 0.1% Tween-20, chaperones |
| Inactive protein | Misfolding, missing cofactors | Slow translation (use rare codons!) | Add GroEL/ES, DnaK/J |
| Truncation | Rare codon clusters, mRNA instability | Remove AGG/AGA/CUA clusters | Supplement rare tRNAs |
| Degradation | Proteolysis | N-terminal Met-Ala | Add protease inhibitors |
Codon Optimization for CFPS
Codons to Avoid in E. coli CFPS
| Codon | Amino Acid | Issue | tRNA Abundance |
|---|---|---|---|
| AGG | Arg | Very rare, stalling | 0.2% |
| AGA | Arg | Very rare, stalling | 0.4% |
| CUA | Leu | Low abundance | 0.4% |
| AUA | Ile | Rare | 0.5% |
| CGA | Arg | Inefficient decoding | 0.6% |
| CCC | Pro | Can cause pausing | 0.5% |
| GGA | Gly | Moderate | 1.1% |
Design Rules
- First 30 codons: Most critical - use only high-frequency codons
- Rare codon clusters: Avoid 2+ rare codons within 10 nt
- Rare codon content: Keep overall <5% of coding sequence
- GC content: Target 40-60% for balanced expression
- Avoid runs: No >6 consecutive G or C residues (secondary structure)
- Strategic slow codons: Place rare codons between domains (aids folding!)
When to Use Rare Codons
- Domain boundaries (allow cotranslational folding)
- Before complex structural elements
- When protein is prone to misfolding
mRNA Template Design
5' UTR Optimization
| Element | Optimal Design | Impact |
|---|---|---|
| RBS (SD sequence) | AGGAGG, 7-9 nt from start | Ribosome binding |
| Spacing | 7 nt between SD and AUG | Translation initiation |
| Secondary structure | ΔG > -5 kcal/mol | Accessibility |
| Upstream AUG | Avoid (causes false starts) | Reduces truncations |
Secondary Structure Targets
| Region | Ideal ΔG | Impact |
|---|---|---|
| -30 to +30 around AUG | > -5 kcal/mol | Translation initiation |
| Full 5' UTR | > -10 kcal/mol | Ribosome loading |
| RBS accessibility | Unpaired | Critical |
Template Format
| Format | Advantages | Disadvantages |
|---|---|---|
| Plasmid | Stable, high yield | Requires cloning |
| Linear PCR | Fast, no cloning | May need stabilization |
| mRNA | Direct translation | Unstable, expensive |
Disulfide Bond Formation
System Capabilities
| System | Native Disulfide Support | Additives Needed |
|---|---|---|
| Standard E. coli extract | Poor (DTT present) | IAM, PDI, GSSG/GSH |
| Oxidizing E. coli extract | Good | Pre-oxidized glutathione |
| Wheat germ | Moderate | Lower DTT, add PDI |
| PURE system | Minimal | Full oxidative system |
| Insect/Mammalian | Good | Microsome membranes |
Oxidative Folding Protocol (E. coli extract)
1. Deplete DTT from extract (dialysis or treatment with IAM 5 mM)
2. Add oxidized/reduced glutathione: 4 mM GSSG, 1 mM GSH (4:1 ratio)
3. Add 10 μM PDI (protein disulfide isomerase)
4. Optional: Add 5 μM DsbC (disulfide isomerase)
5. Express at 25°C (not 37°C) for better folding
6. Incubation time: 4-6 hoursDisulfide-Rich Protein Tips
- Start with wheat germ or oxidizing extract
- Use PURE system for precise control
- Consider co-expression of PDI/DsbC
- Verify by non-reducing SDS-PAGE
Expression Prediction from Sequence
| Feature | Good | Marginal | Bad |
|---|---|---|---|
| Rare codon content | <3% | 3-8% | >10% |
| First 30 codons rare | 0 | 1-2 | >2 |
| GC content | 45-55% | 35-45% or 55-65% | <30% or >70% |
| 5' UTR ΔG | > -3 kcal/mol | -3 to -8 | < -10 kcal/mol |
| Hydrophobic stretches | <5 consecutive | 5-7 | >8 consecutive |
| N-terminal residue | Met-Ala, Met-Ser, Met-Gly | Met-Val, Met-Thr | Met-Arg, Met-Lys |
| Cysteine pairs | Paired (even number) | Mixed | Odd number (free thiols) |
Solubility Enhancement Strategies
Fusion Tags (ranked by effectiveness)
| Tag | Size | Solubility Enhancement | Cleavage | Notes |
|---|---|---|---|---|
| MBP | 40 kDa | Excellent | TEV, Factor Xa | Best overall |
| SUMO | 11 kDa | Very Good | SUMO protease | Native N-terminus after cleavage |
| NusA | 55 kDa | Excellent | - | Large size |
| Trx | 12 kDa | Good | Enterokinase | For disulfide proteins |
| GST | 26 kDa | Moderate | - | Dimeric |
| His₆ | 1 kDa | Minimal | - | Mainly for purification |
Show full SKILL.md (404 more words)Show less
Buffer Additives for Solubility
| Additive | Concentration | Mechanism |
|---|---|---|
| Trehalose | 50-100 mM | Chemical chaperone |
| Glycerol | 5-10% | Reduces hydrophobic aggregation |
| L-Arginine | 50-100 mM | Suppresses aggregation |
| Tween-20 | 0.05-0.1% | Prevents surface adsorption |
| Proline | 50 mM | Osmolyte stabilization |
Chaperone Supplementation
| Chaperone System | Target Problem | Concentration |
|---|---|---|
| GroEL/GroES | General folding | 1-2 μM |
| DnaK/DnaJ/GrpE | Aggregation-prone | 1 μM each |
| Trigger Factor | Nascent chain | 1-2 μM |
| ClpB | Aggregate resolubilization | 0.5 μM |
Temperature Optimization
| Temperature | Use Case | Trade-offs |
|---|---|---|
| 37°C | Fast expression, stable proteins | Higher aggregation risk |
| 30°C | Balanced (default) | Good compromise |
| 25°C | Disulfide proteins, complex folds | Slower, better folding |
| 18-20°C | Aggregation-prone proteins | Much slower, best folding |
| 16°C | Cold-shock proteins | Very slow, specialized |
E. coli Extract Preparation (Key Variables)
| Variable | Impact | Optimal Range |
|---|---|---|
| Cell density at harvest | Ribosome content | OD₆₀₀ 2.5-3.5 |
| Lysis method | Extract activity | Sonication, bead beating |
| Run-off reaction | Removes endogenous mRNA | 20-80 min at 37°C |
| Mg²⁺ concentration | Translation fidelity | 10-18 mM |
| K⁺ concentration | Translation rate | 150-200 mM |
| Energy system | Sustained synthesis | ATP/GTP, creatine phosphate |
PURE System Specifics
Advantages
- Defined composition (no proteases/nucleases)
- Linear DNA templates work well
- Unnatural amino acid incorporation
- Reproducible between batches
Limitations
- No chaperones (add separately)
- No post-translational modifications
- Lower yields than crude extracts
- Higher cost
When to Use PURE
- Unnatural amino acid incorporation
- Studying translation mechanisms
- "Clean" proteins needed
- Protease-sensitive targets
- Linear template expression
Common Artifacts and Solutions
Low Molecular Weight Bands
Causes: Premature termination, proteolysis, internal initiation Solutions:
- Optimize rare codon clusters
- Add protease inhibitors
- Check for internal AUG codons
- Use PURE system
Higher MW Bands
Causes: Incomplete termination, read-through, aggregation Solutions:
- Ensure strong stop codon (UAA preferred)
- Check template 3' end
- Add release factors (RF1/RF2)
- Reduce protein concentration
No Soluble Protein
Causes: Aggregation during synthesis Solutions:
- Lower temperature (25°C → 18°C)
- Add chaperones
- Use solubility tag
- Optimize translation rate
References
CFPS Overview
- User's Guide to CFPS - PMC
- Optimising Protein Synthesis in Cell-Free Systems - PMC
- CFPS Systems Comparison - PMC
Extract Preparation
- Crude Extract Preparation - MDPI Methods
- Simple Rapid Cell-Free Lysate - PLOS One
- High-Throughput Extract Preparation - Nature Scientific Reports
PURE System
Wheat Germ
Codon Optimization
- Rare Codons and Solubility - PMC
- Codon Influence on Expression - Nature
- Synonymous Codon Substitutions Perturb Folding - PNAS
Disulfide Formation
Solubility Tags
Temperature Effects
© adaptyvbio, MIT. 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/cell-free-expression of adaptyvbio/protein-design-skills.
Open the folder on GitHubat commit 59dd633
Used in 3 other repositories
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in adaptyvbio/protein-design-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Cell Free Expression 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 |
|---|---|---|---|---|---|---|
| Cell Free Expression this skilladaptyvbio/protein-design-skills | 163 | 3 repos | ~2.8k | 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 | |
| Pymol VisualizationChatMol/ChatMol | 372 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Complexa Binder DesignNVIDIA-BioNeMo/bionemo-agent-toolkit | 478 | — | ~3.1k | Automated safety check: Notes | Apache-2.0 | |
| DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3k | Automated safety check: Notes | MIT | |
| Biopipelineslocbp-uzh/biopipelines | 109 | — | ~2.4k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Cell Free Expression
What does Cell Free Expression do?
Guidance for cell-free protein synthesis (CFPS) optimization. Cell Free Expression is an agent skill from adaptyvbio/protein-design-skills. Guidance for cell-free protein synthesis (CFPS) optimization.
When should I use Cell Free Expression?
Cell Free Expression fits situations like: planning CFPS experiments; troubleshooting low yield; optimizing DNA template design for CFPS; expressing difficult proteins (disulfide-rich.
How do I install Cell Free Expression in Claude Code?
Run `npx skills add adaptyvbio/protein-design-skills --skill cell-free-expression -a claude-code`. Or copy the skill folder (skills/cell-free-expression in adaptyvbio/protein-design-skills) into .claude/skills/cell-free-expression in your project. Claude Code loads it when a task matches its description.
How do I install Cell Free Expression in Codex?
Run `npx skills add adaptyvbio/protein-design-skills --skill cell-free-expression -a codex`. Or copy the skill folder (skills/cell-free-expression in adaptyvbio/protein-design-skills) into .agents/skills/cell-free-expression in your project. Codex loads it when a task matches its description.
Can I use Cell Free Expression 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 adaptyvbio/protein-design-skills --skill cell-free-expression -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cell-free-expression, .gemini/skills/cell-free-expression, .github/skills/cell-free-expression and .opencode/skills/cell-free-expression in your project.
What does Cell Free Expression need to run?
SKILL.md names no scripts, command-line tools or credentials: Cell Free Expression is instructions for the agent only.
Does Cell Free Expression access the network?
SKILL.md names 8 domains. As links in the text: pmc.ncbi.nlm.nih.gov, nature.com, ncbi.nlm.nih.gov, mdpi.com, journals.plos.org, febs.onlinelibrary.wiley.com, pnas.org and frontiersin.org. This is read from the text; nothing was executed.
Is Cell Free Expression 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 Cell Free Expression use?
Cell Free Expression is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Cell Free Expression use?
About 2.8k tokens (SKILL.md is roughly 11k 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 Cell Free Expression?
Skills that share tags, products or a category with Cell Free Expression: Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars), Pymol Visualization (ChatMol/ChatMol, 372 stars), Complexa Binder Design (NVIDIA-BioNeMo/bionemo-agent-toolkit, 478 stars) and DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cell Free Expression?
adaptyvbio (a GitHub organization) maintains it in adaptyvbio/protein-design-skills, which has 163 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on June 11, 2026.
Source: adaptyvbio/protein-design-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.