Inspect a local PDB structure, summarize chains and residue composition, and identify protein atoms near a user-specified ligand or pocket center. Use for reproducible first-pass structure and binding-site inspection before heavier modeling.
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Use this method for a transparent first-pass analysis of a local PDB structure. It does not predict affinity, docking poses, or biological function.
$SCIENCEDISCOVERY_SKILLS_DIR/structure-pocket-inspection/scripts/inspect_pdb.py with explicit workspace paths and options. The complete package is already mounted read-only when the execution sandbox starts; do not copy the script, read its source into context, or search the filesystem for another copy. If the workspace already contains an equivalent user-owned script, invoke that script instead. Do not copy the structure into another proprietary format.The corresponding bundled-script arguments for residues within 5 Å of ATP are:
python "$SCIENCEDISCOVERY_SKILLS_DIR/structure-pocket-inspection/scripts/inspect_pdb.py" structure.pdb --ligand ATP --cutoff 5 --output pocket.json
For residues within 6 Å of a known pocket center:
python "$SCIENCEDISCOVERY_SKILLS_DIR/structure-pocket-inspection/scripts/inspect_pdb.py" structure.pdb --center 12.4 8.1 -3.0 --cutoff 6 --output pocket.json
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Prepare, launch, monitor, and summarize the real RFdiffusion to ProteinMPNN to Protenix antibody pipeline on a local or remote ScienceDiscovery Runner with sandboxed Ascend NPUs.
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Independent multi-dimensional assessor for material design candidates. Loads configurable scoring rubrics to evaluate candidates from different expert perspectives. Each dispatch produces structured scores, pros/cons, and verification data without sharing results with other assessors.
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Read, diagnose, and change the CI pipeline: GitHub Actions on pull requests, the merge queue, the nightly schedule and the release tag. Use when a job fails, when editing .github/workflows/, when asking which layer runs what, when reproducing a pipeline failure locally, or when a job needs the bubblewrap sandbox. Running the layers before proposing a change, and reading the result a proposal receives, belong to create-github-pr.
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Verify cited paper identity and decide whether claims in an Artifact are supported by their linked Evidence using a governed source snapshot.
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Use this skill when you need to write and execute Python/R code to process, transform, and analyze data, delivering reproducible computational results with complete code-level methodology documentation. Supports statistical analysis, data transformation, visualization, method justification, and structured result output.
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Check whether numeric claims marked with Evidence aliases in an Artifact agree with the linked Evidence content and context.
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