Export Proposed Terms

SkillDev tools

Export top-level ai-gene-review `proposed_new_terms` entries to a deterministic TSV table.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Export Proposed Terms skill

What this skill tells your AI

The instructions your AI receives, as published by ai4curation/ai-gene-review in .claude/skills/export-proposed-terms/SKILL.md and read by ahel’s review.

Use this skill when the user asks for a TSV or tabular extract of ontology term requests recorded in gene review YAML files.

Run the helper from the repository root:

uv run python src/ai_gene_review/tools/export_proposed_terms.py -o reports/proposed_new_terms.tsv

Pass files or directories after the options to restrict the export. With no inputs, the helper scans genes/**/*-ai-review.yaml.

The TSV defaults to reports/proposed_new_terms.tsv. It has one row per top-level proposed_new_terms entry and skips reviews where proposed_new_terms is empty. It includes:

  • source review fields: source_path, organism, gene_directory, review_id, gene_symbol, taxon_id, taxon_label
  • proposal fields: term_index, proposed_name, proposed_definition, justification, proposed_parent_id, proposed_parent_label
  • structured evidence fields serialized as JSON: proposed_mappings, supported_by

The exporter intentionally ignores knowledge_gaps[].proposed_terms; those are nested gap-specific proposals, not the review's top-level ontology request list. If the user explicitly asks for gap proposals too, write a separate ad hoc extract with a column that distinguishes top-level terms from gap terms.

For custom column order, filtering, or aggregation, treat the generated TSV as a staging table and post-process it with Python's csv module or pandas. Preserve TSV safety by keeping embedded tabs and newlines out of scalar cells.

Treat the TSV as a read-only reporting view, not a round-trip editing source. Scalar columns are whitespace-normalized for tabular readability; nested proposed_mappings and supported_by values are compact JSON for inspection. When updating a review, copy exact supporting_text from the source YAML or publication cache, not from a TSV extract.

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GitHub stars
24
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Last commit
Oct 2026
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Item type
skill
Key
export-proposed-terms
Source
github.com/ai4curation/ai-gene-review