| name | mdh-reference |
| description | Rossum Master Data Hub (MDH) API reference and matching query design guide. Covers dataset CRUD, fuzzy search, hook configuration model (MatchConfig, mapping, result actions, query cascades), query design rules, score normalization, and real-world matching examples. Use when building or debugging MDH matching configurations, designing query cascades, or working with the MDH API. |
| user-invocable | false |
Master Data Hub (MDH) Reference
This skill provides comprehensive reference documentation for Rossum's Master Data Hub — the matching engine that connects extracted document data to master data records. It covers the MDH management API, the hook configuration model, and query design patterns.
Reference files:
- mdh-api-reference.md — MDH API endpoints (dataset CRUD, fuzzy search, operation status) and hook configuration schema (MatchConfig, DMDatasetSource, Mapping, ResultActions, query cascade model)
- mdh-matching-queries.md — Query design rules (DO/DON'T), score normalization patterns, unique-result filters, GL coding dropdown pre-selection, real-world examples (supplier matching, PO line items, delivery address resolution), and Atlas Search index recommendations
Use this knowledge when:
- Building MDH matching configurations (hook JSON with source, mapping, result_actions)
- Designing query cascades (exact → fuzzy → fallback)
- Using score normalization or
$setWindowFields unique-result patterns
- Configuring memorization via
$unionWith patterns
- Managing MDH datasets via the API (upload, replace, update, delete)
- Enabling fuzzy search on datasets
- Debugging matching hook configurations
Mandatory pre-flight for any $search query. Before shipping or debugging a $search stage, list the search indexes on the collection (data_storage_list_search_indexes) and confirm the named index exists and maps every field you reference. A missing or misnamed index returns zero results silently with status: completed — the hardest MDH failure mode to diagnose. Full recipe in mdh-matching-queries.md → Atlas Search Index Pre-flight.
When writing or debugging queries, if the dataset structure is not already known from context, try to discover it using the rossum-api MCP tools: data_storage_list_collections to find available collections and data_storage_aggregate with [{"$sample": {"size": 1}}] to retrieve a sample record. Fall back to asking the user only if the MCP tools are not available.
