docs: salvage USPTO and gget skills

skills/scientific-pkg-gget/SKILL.md

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+---
+name: gget
+description: gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
+origin: community
+---
+
+# gget
+
+Use this skill when a task needs quick bioinformatics lookup across genomic
+reference databases with the `gget` CLI or Python package.
+
+## When to Use
+
+- Finding Ensembl IDs, gene metadata, transcript details, or sequences.
+- Running quick BLAST or BLAT lookups without building a full local pipeline.
+- Fetching reference genome links and annotations from Ensembl.
+- Querying protein structure, pathway, cancer, expression, or disease-association
+  modules through a single interface.
+- Creating a reproducible first-pass evidence log before moving to heavier
+  tools such as Biopython, Snakemake, Nextflow, BLAST+, or database-specific
+  clients.
+
+Use a dedicated workflow instead of `gget` when the task requires regulated
+clinical interpretation, high-throughput production pipelines, or fine-grained
+control over database versions and local indexes.
+
+## Installation
+
+Use a clean Python environment.
+
+```bash
+python -m venv .venv
+. .venv/bin/activate
+python -m pip install --upgrade pip
+python -m pip install --upgrade gget
+gget --help
+```
+
+If `uv` is available:
+
+```bash
+uv venv
+. .venv/bin/activate
+uv pip install gget
+```
+
+Before relying on an older environment, upgrade `gget` and re-check the module
+docs. The upstream databases queried by `gget` change over time.
+
+## Basic Patterns
+
+CLI shape:
+
+```bash
+gget <module> [arguments] [options]
+```
+
+Python shape:
+
+```python
+import gget
+
+result = gget.search(["BRCA1"], species="human")
+print(result)
+```
+
+Common workflow:
+
+1. Identify the species, assembly, gene ID type, and database needed.
+2. Check the current module documentation for arguments.
+3. Run a small query first.
+4. Save output with an explicit filename and date.
+5. Record module name, version, arguments, and database assumptions.
+
+## Common Modules
+
+Use current upstream docs for exact arguments. These modules are common first
+choices:
+
+- `gget search`: find Ensembl IDs from search terms.
+- `gget info`: retrieve metadata for Ensembl, UniProt, or related IDs.
+- `gget seq`: fetch nucleotide or amino-acid sequences.
+- `gget ref`: retrieve reference genome download links.
+- `gget blast`: run a quick BLAST query.
+- `gget blat`: locate a sequence against supported genome assemblies.
+- `gget muscle`: run multiple sequence alignment.
+- `gget diamond`: run local sequence alignment against reference sequences.
+- `gget alphafold` and `gget pdb`: inspect protein-structure references.
+- `gget enrichr`, `gget opentargets`, `gget archs4`, `gget bgee`, `gget cbio`,
+  and `gget cosmic`: explore enrichment, target, expression, cancer, and disease
+  association data.
+
+Do not assume every module supports every Python version or dependency set.
+Some optional scientific dependencies have narrower version support than the
+core package.
+
+## Quick Examples
+
+Find genes:
+
+```bash
+gget search -s human brca1 dna repair -o brca1-search.json
+```
+
+Fetch gene metadata:
+
+```bash
+gget info ENSG00000012048 -o brca1-info.json
+```
+
+Fetch a sequence:
+
+```bash
+gget seq ENSG00000012048 -o brca1-seq.fa
+```
+
+Run a small BLAST query:
+
+```bash
+gget blast "MEEPQSDPSVEPPLSQETFSDLWKLLPEN" -l 10 -o blast-results.json
+```
+
+Python example:
+
+```python
+import gget
+
+genes = gget.search(["BRCA1", "DNA repair"], species="human")
+info = gget.info(["ENSG00000012048"])
+sequence = gget.seq("ENSG00000012048")
+```
+
+## Reproducibility Log
+
+For scientific outputs, include enough metadata to replay the query.
+
+```markdown
+| Date | gget version | Module | Query | Species/assembly | Output | Notes |
+| --- | --- | --- | --- | --- | --- | --- |
+| 2026-05-11 | `gget --version` | search | `BRCA1 DNA repair` | human | `brca1-search.json` | Docs checked before run |
+```
+
+Also record:
+
+- Python version and environment manager.
+- Any optional dependency installed through `gget setup`.
+- Database-specific identifiers returned by the query.
+- Whether output is JSON, CSV, FASTA, or a DataFrame export.
+- Any failures that were resolved by upgrading `gget`.
+
+## Review Checklist
+
+- Did you upgrade or verify the installed `gget` version?
+- Did you check the current upstream module docs before using arguments?
+- Is the species or assembly explicit?
+- Are identifiers preserved exactly, including Ensembl/UniProt prefixes?
+- Is the result labeled as database output rather than clinical interpretation?
+- Is the query reproducible from the saved command or Python snippet?
+- Are optional dependencies installed in an isolated environment?
+
+## References
+
+- [gget documentation](https://pachterlab.github.io/gget/)
+- [gget updates](https://pachterlab.github.io/gget/en/updates.html)
+- [gget GitHub repository](https://github.com/pachterlab/gget)
+- [gget Bioinformatics paper](https://doi.org/10.1093/bioinformatics/btac836)