"Use for PaddleHelix protein sequence pretraining, prediction,
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill protein-sequence-function --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Protein Sequence Function?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-protein-sequence-function)More formats (shields.io, HTML) on the badges page.
---
name: protein-sequence-function
description: "Use for PaddleHelix protein sequence pretraining, prediction,
protein function workflows, tokenizer/model guidance, and safe protein input
validation."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
---
# Protein Sequence Function
Use this sub-skill when the task asks about PaddleHelix TAPE-style protein sequence models, protein property prediction, protein function prediction apps, protein sequence tokenization, FASTA/plain sequence validation, PPI routing, or HelixProtX high-level protein modality routing.
## Route First
- Use this sub-skill for TAPE train/eval/predict command construction, model config checks, `ProteinTokenizer` behavior, and protein sequence model-family orientation.
- Use this sub-skill for DeepFRI, ProteinSIGN, and PTHL protein function prediction command anatomy, data roles, checkpoints, and missing-argument diagnosis.
- Route biomolecular 3D structure prediction, HelixFold, and HelixFold3 input/output planning to `../structure-prediction/SKILL.md`.
- Route LinearRNA folding/partition tasks to `../linear-rna/SKILL.md`; route compound/drug workflows to `../compound-drug-discovery/SKILL.md`.
- Treat PPI S2F requests as not-yet-released in the scoped PaddleHelix evidence; explain the gap and ask whether the user wants adjacent sequence/function guidance instead.
## Safe First Steps
1. Classify the request as TAPE sequence modeling, graph-based function prediction, PPI, or HelixProtX multimodal protein routing.
2. Validate sequences and model config before constructing a training/eval/predict command.
3. Check that all user-provided data, checkpoint, graph, and label paths are explicit; do not assume app defaults are valid.
4. Confirm before starting downloads, training, GPU/distributed jobs, graph preprocessing over PDB, or HelixProtX demos.
## Bundled Helper
Use the safe validator before heavyweight commands. It performs local parsing only and never downloads data, trains, mutates checkpoints, or imports Paddle/PGL.
```bash
python sub-skills/protein-sequence-function/scripts/validate_protein_inputs.py \
--sequence ACDJX \
--show-token-ids
```
For TAPE prediction preflight, add `--workflow tape-predict`, `--config`, `--predict-model`, and either `--predict-data`, `--fasta`, or `--sequence`. For function-prediction checks, use `--workflow function-test` with `--model-name`, `--label-data-path`, `--test-file`, and `--protein-chain-graphs`; missing `--model-name` or `--label-data-path` is a real evaluation blocker.
## Reference Map
- `references/workflows.md`: TAPE and function-prediction command anatomy, data/checkpoint/model roles, PPI and HelixProtX routing.
- `references/data-formats.md`: sequence, tokenizer, TAPE NPZ/config, function-prediction graph and label formats.
- `references/api-reference.md`: `ProteinTokenizer`, protein sequence model class family, task heads, criteria, metrics, and dataloader orientation.
- `references/troubleshooting.md`: unknown residues, missing data/checkpoints, Paddle/PGL versions, GPU/distributed flags, and PDB graph requirements.
- `scripts/validate_protein_inputs.py`: safe local validator for FASTA/plain sequences, token IDs, TAPE configs, optional JSON/config parsing, and function workflow path checks.
## Evidence Labels
Distilled from these repo-relative evidence labels: `apps/pretrained_protein/tape/`, `apps/protein_function_prediction/`, `apps/protein_protein_interaction/`, `apps/helixprotx/`, `pahelix/utils/protein_tools.py`, `pahelix/model_zoo/protein_sequence_model.py`, and `tutorials/protein_pretrain_and_property_prediction_tutorial.ipynb`.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!