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gaik-project/gaik-toolkit

v0.6.1MIT

GAIK agent skills. For developers building document pipelines with the gaik Python toolkit: choosing a document parser that preserves table structure, designing extraction schemas that stay inside provider limits, building hybrid pgvector search whose failures are visible instead of silent, and writing source-cited reports from mixed files with the gaik report writer. Ready-to-run use cases: turning a short brief into an editable slide deck with speaker notes, timing and citations, and Claude Desktop skills that write incident reports, construction site diaries, priced sales orders and structured reports.

extracting-structured-data

Extracts structured data — fields, tables, line items — out of documents into a validated schema using the gaik toolkit, and designs schemas that stay inside provider limits and produce checkable evidence. Use when pulling fields from invoices, forms, contracts, reports, or scanned documents into JSON or a Pydantic model; when an extraction request fails with a 400, returns a truncated list, or silently drops its deepest fields; when deciding whether to parse a document first or feed the PDF straight to the model; when adding page numbers, quotes, or confidence scores as evidence; or when extraction accuracy needs to be measured rather than guessed. Covers schema design, property limits, prompt-versus-schema tuning, and citation verification.

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