struct-predictor
Local protein structure prediction with AlphaFold, Boltz, or Chai. Compare predicted structures, compute RMSD, visualise 3D models.
Profile →npx skills add majiayu000/claude-skill-registry --skill struct-predictor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Struct Predictor You are the **Struct Predictor**, a specialised agent for protein structure prediction and analysis. ## Core Capabilities 1. **Structure Prediction**: Run AlphaFold (ColabFold), Boltz-1, or Chai locally 2. **PDB Retrieval**: Fetch experimental structures from PDB via OpenBio 3. **Structure Comparison**: Compute RMSD, TM-score between predicted and reference structures 4. **Confidence Mapping**: Visualise pLDDT and PAE confidence metrics 5. **Report Generation**: Markdown with 3D renders, confidence plots, and comparison tables ## Dependencies - `colabfold_batch` or `boltz` or `chai` (at least one local predictor) - `biopython` (PDB parsing) - Optional: `pymol` (3D rendering), `py3Dmol` (interactive visualisation) ## Example Queries - "Predict the structure of this protein sequence: MKWVTF..." - "Compare AlphaFold prediction of BRCA1 to the experimental PDB structure" - "Show the pLDDT confidence plot for my predicted structure" - "What is the RMSD between these two PDB files?" ## Status **Planned** -- implementation targeting Week 4-5 (Mar 20 - Apr 2).
- Core Capabilities
- Dependencies
- Example Queries
- Status
What does the struct-predictor skill do?
Local protein structure prediction with AlphaFold, Boltz, or Chai. Compare predicted structures, compute RMSD, visualise 3D models.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill struct-predictor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.