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name: specialized-workflows description: "Operate gget's viral dataset, mutation-generation, optional setup, and legacy GPT workflows with explicit filters, file contracts, validation, and side-effect boundaries." disable-model-invocation: true metadata: disco-role: operating license: BSD 2-Clause

Specialized workflows

Use this skill for four gget entry points:

• gget.virus: retrieve and filter viral sequence datasets from NCBI Virus.
• gget.mutate: apply standard nucleotide mutation annotations to FASTA or in-memory nucleotide sequences.
• gget.setup: install/download optional dependencies or ELM data.
• gget.gpt: call the legacy OpenAI ChatCompletion wrapper.

Read the matching reference before a non-trivial run: virus workflow, mutation contract, setup and GPT, and troubleshooting. For a safe preflight of a FASTA/table pair, use validate_mutation_inputs.py. It reads inputs and prints JSON; it never mutates them, downloads data, installs packages, or calls an API.

Route first

• Route general Ensembl/NCBI sequence retrieval, translation, alignment, BLAST, or related sequence operations to sequence-tools.
• Route cancer mutation database lookup or cancer structure interpretation to disease-structure; use mutate only to transform sequences from an already-selected mutation table.
• Keep virus for viral dataset retrieval/filtering, not arbitrary taxonomy or generic FASTA manipulation.

Choose the workflow

1. Viral retrieval. Start with a taxon name, taxon ID, accession, a space-separated accession list, or a one-accession-per-line text file. Set is_accession=True for accession forms. For SARS-CoV-2 or Alphainfluenza, use the explicit optimized flag for accession queries.
2. Mutation generation. Start with nucleotide FASTA (or a string/list) and a mutation string, list, CSV/TSV, or DataFrame. Establish the sequence-ID join before invoking the transform.
3. Optional setup. Treat setup as an installation/download operation, not a harmless probe. Inspect the target environment and obtain approval before running it.
4. Legacy GPT. Treat gpt as a credentialed, billable, unmaintained compatibility wrapper. Do not use it without an explicit API key and confirmation of the old OpenAI client contract.

Viral run recipe

• Select narrow filters before downloading. virus validates inputs, obtains server-side metadata (or uses cached metadata), applies local metadata filters, performs GenBank-dependent filtering when needed, downloads only surviving accessions, then applies sequence-dependent filters.
• Use outfolder explicitly. Expect FASTA plus metadata CSV/JSONL and command_summary.txt; GenBank mode adds detailed CSV and full XML/CSV.
• For incremental work, pass a baseline CSV/JSONL/JSON/text accession file. With merge_results=True, inspect the merged CSV; with False, inspect the new-only CSV and retained baseline reference. Never overwrite the source baseline as a recovery shortcut.
• Confirm output counts agree across FASTA, final metadata JSONL, and CSV. Read the summary's counts for API records, metadata survivors, GenBank survivors, final sequences, filter exclusions, and failed operations.

Mutation run recipe

• Ensure every mutation-table seq_ID matches the FASTA identifier after gget's normalization: first token only, with a dot/version suffix removed. A missing join is an input error, not permission to guess.
• Use HGVS-like nucleotide annotations such as c.35G>A, ranges with del/ins/delins, dup, or inv; verify the wild-type base for a substitution. Use k to bound retained flanks (default 30).
• Return a list when out=None and update_df=False; write mutant FASTA when out is supplied. Output headers are >[seq_ID]:[mut_ID] in the current implementation (the older docs show an underscore; follow the live output).
• Request update_df=True for mutation annotations and sequences in a CSV/TSV output. Full-sequence and translation columns require store_full_sequences=True; translation uses the requested nucleotide frame and emits X for unknown/incomplete codons. Keep the original FASTA/table; write to a new output path.

Setup and GPT boundaries

• Supported setup module names are alphafold, cellxgene, elm, gpt, and cbio. It may install with uv or pip, download ELM files with curl, clone and patch AlphaFold dependencies, and download large model parameters.
• For ELM, omit out if gget.elm must find the downloaded files; a custom out is an independent copy and is not used by the module. For AlphaFold, expect platform/dependency/model-size constraints and prefer a dedicated environment.
• gpt uses api_key directly, sets openai.api_key, calls openai.ChatCompletion.create, returns text with a trailing newline, and optionally writes the text to out. The wrapper targets openai<=0.28.1; newer clients commonly lack this endpoint. Never place keys in files or command history, and do not send sensitive data in prompts.

Validate and recover

• Before network or credentialed work, run the mutation preflight and inspect its JSON errors. For virus runs, validate date ranges, mutually exclusive host/env_source, storage, and intended output location first.
• Do not run real downloads, setup, or GPT calls in a dry-run. Use mocked API responses or tiny local fixtures for tests. On a viral API failure, preserve the partial JSONL and resume with it as baseline_metadata; on a mutation mismatch, fix IDs or the table and rerun to a new FASTA; on setup/GPT errors, inspect package/version and environment state before reinstalling.
• Stop and report when a service is unavailable, a credential is absent, the requested dataset is too large, or a required dependency would alter the environment without approval. See troubleshooting for concrete recovery paths.