Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Manages protein structure prediction jobs through the FastFold Jobs API. Handles the full lifecycle: authenticate, submit a fold job, poll until complete, then retrieve CIF/PDB files, quality metrics, and 3D viewer links. Works with single proteins, multi-chain complexes, RNA, DNA, and ligand sequences.
The bundled scripts handle polling, error states, and result parsing so you don't have to write that boilerplate yourself.
When to use it
- Folding a novel protein sequence to predict its 3D structure
- Automating batch fold submissions and waiting for results in a script
- Downloading CIF files from completed jobs for use in molecular visualization tools
- Checking pTM and ipTM confidence scores after a multi-chain complex prediction
- Getting a shareable FastFold viewer link for a completed fold job
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Fold this protein sequence MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKT and give me the viewer link
- 1Check that FASTFOLD_API_KEY is set in the environment or .env file
- 2Run create_job.py with the sequence and a job name to POST to /v1/jobs
- 3Run wait_for_completion.py with the returned job ID, polling every 5 seconds until status is COMPLETED
- 4Run fetch_results.py to retrieve meanPLLDT, ptm_score, and artifact URLs
- 5Run get_viewer_link.py to build the FastFold cloud viewer URL
Job completed with meanPLLDT 87.3, ptm_score 0.81. CIF available at the signed URL. Viewer: https://cloud.fastfold.ai/mol/new?from=jobs&job_id=<uuid>
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.