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Ross ERP Data Dictionary

search_all

Cross-domain search in one call — spans schema objects, columns, UI facilities and programs at once. Use this when you don't yet know which layer a term lives in (e.g. 'check register' is a screen, a program and a table). Scope to one layer with type = object | column | facility | program (default all); limit is per domain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoRestrict to one domain (default all). 'table' is accepted as an alias for object.
limitNoMax results per domain (default 25)
queryYesSearch text, e.g. check register or posting_date

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description discloses cross-domain behavior, per-domain limit handling, and type scoping. It does not describe output structure or side effects, but for a read-only search tool this is adequate and goes beyond the schema by explaining the multi-domain granularity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, followed by usage guidance. Every word earns its place; no filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (3 params, 1 required) and the description covers purpose, usage context, and parameter behavior. It lacks output format details, but with no output schema and read-only nature, this is acceptable. It is complete enough for an agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all three parameters with descriptions, so the baseline is 3. The description adds the example phrase and reiterates the 'limit is per domain' and 'type default all' nuances already present in the schema. It does not provide meaningful additional parameter semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a cross-domain search across schema objects, columns, UI facilities, and programs in one call. It uses a specific verb (search), names the resources (objects, columns, facilities, programs), and distinguishes it from per-domain sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to use this tool when you don't know which layer a term lives in, with a concrete example. It does not name alternative tools or state when not to use it, but the use case is clear and the per-domain scope option is described.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: list/lookup/search pairs are separated by summary vs full detail, exact match vs fuzzy search, and domain scope. Cross-reference tools are explicitly paired as reverse lookups (facility_programs/program_facilities, table_facilities/table_programs), eliminating ambiguity. Minor overlaps like find_column vs search_columns and get_ddl vs lookup_table are well-differentiated by their descriptions.

Naming Consistency4/5

The naming is largely predictable with list_ for browsing, lookup_ for full detail, search_ for searching, and _stats for overviews. Cross-links follow a noun_noun pattern (facility_programs, table_facilities). Exceptions like find_column, get_ddl, graph_neighbors, and path_between are still intuitive and do not create confusion, though they deviate from the dominant verb-first pattern.

Tool Count3/5

At 21 tools, the set sits in the 16-25 range that feels heavy. However, each tool serves a distinct function across schema, facilities, programs, columns, and graph traversal, so the count is justified for a comprehensive data dictionary. It is not as tightly scoped as a typical CRUD server, but the breadth is necessary for the domain.

Completeness5/5

The tool set provides complete coverage for a read-only data dictionary: browsing, searching, full details, and cross-references for every entity type (objects, columns, facilities, programs), plus graph utilities. There are no obvious dead ends or missing operations; stats and search-all tools further enhance orientation and cross-domain discovery.

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