com.acjlabs/catalog-normalizer

repo:https://github.com/acjlabs/catalog-normalizer

Catalog attribute normalizer, taxonomy-grounded — no fabricated Google/Shopify category IDs.

transport:: remote
credential class:: unreachable
repo:: https://github.com/acjlabs/catalog-normalizer

Owner verification

Not yet verified. Verifying proves you control this server and is free, permanently — it never changes a published score.

Start verification →

Tools

normalize_catalog
Normalizes a batch of catalog products (attribute canonicalization/extraction + category-path mapping into the requested target taxonomies: google, shopify, amazon). Returns one result per input product, same order: a NormalizedProduct on success, or { error, source_title } if that specific product's classification failed — one product's failure never voids the rest of the batch. attributes is keyed by a controlled vocabulary (size, color, material, gender, sleeve_length — unrecognized keys are dropped, not passed through under a model-chosen name) and each value carries provenance: "canonicalized" means it came from your own raw_attributes input for that product (deterministic cleanup only, no recall); "extracted" means the model inferred it from the title/description and it wasn't in your input — treat extracted values as a suggestion, not a confirmed fact about the product, the same way you'd treat a low-confidence category_paths entry. category_paths for google and shopify is retrieval-grounded against the real, current taxonomy files (not recalled from memory) — measured at 22/24 (91.7%) exact path+leaf_id matches on a 12-product evaluation set; amazon has no comparable public reference file, so it stays best-effort. Each entry's confidence (0-1) and leaf_id (null when not confident it matches a real node) are the honest signal regardless of taxonomy — treat a low-confidence or null-leaf_id result as a suggestion worth a quick human check, not a confirmed classification.
shallow

Embed this server’s score

Tool count and median score across every tool in this server’s corpus — honest in a way a single cherry-picked tool’s badge wouldn’t be.

[![Vouch score](https://vouch.tools/api/servers/0bfc62c3-1ce8-424e-a351-c58ddd9b97dc/badge.svg)](https://vouch.tools/servers/0bfc62c3-1ce8-424e-a351-c58ddd9b97dc)