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recommendation-candidates

Step 1 of recommendation-extraction, for one source at a time. That skill holds the judgement — what counts as a recommendation, and implementation guidance that prints practices rather than recommendations (its Part 1). This one is the mechanical step around it.

Input and output

In: an ingested library/<id>/ entry and, on the second pass, the agent’s l1-recommendation-curation/v1. Out: the candidate work list; once curated, the L1 3.0 graph (l1.json, every node inferred), the proposed exclusions and the warnings.

Steps

  1. Run the Tool with no curation: it writes the work list, every normative sentence with its hints, nothing decided.
  2. The agent writes curation.yaml, one decision per location, following recommendation-extraction Part 1.
  3. Run the Tool again with the curation: it applies the gates and writes the graph. A refusal (a statement that is not verbatim, an unknown location) goes back to step 2.

Tool

l1-recommendation-candidates (smart-base/tools/l1-recommendation-candidates/l1-recommendation-candidates.ts):

bun run smart-base/scripts/l1-recommendation-candidates.ts --entry <library entry> [--curation <curation.yaml>] --out <dir> [--check]

folio-assistant — code under the Apache License 2.0, documentation under CC BY 3.0. Generated schema and API references are rebuilt from source on every push to main.

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