Ross ERP Data Dictionary

list_programs

Browse and filter Ross ERP 8.0 programs (application source, metadata only). Filter by module (ap, gl, ic, sop, ...), type (a=archive, i=inquiry, m=maintenance, r=report, s=server, l=load, u=utility, ...), layer (base | vendor-core), titled (only programs that declare a TITLE id), or a substring of basename/title; paginate with limit/offset. Returns summaries — use lookup_program for full detail.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Substring of basename or title, e.g. check_register
`type`	No	Program-type letter, e.g. r (report), m (maintenance), i (inquiry), s (server)
`layer`	No	Source layer: base \| vendor-core
`limit`	No	Max programs (default 100)
`module`	No	Module filter, e.g. ap, gl, ic, sop
`offset`	No	Pagination offset (default 0)
`titled`	No	Only programs that declare a TITLE program-id (default false)

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses that results are summaries, support pagination via limit/offset, filter by module/type/layer/titled/substring, and that full detail requires lookup_program. It does not cover auth, rate limits, or empty-result behavior, but the core behaviors are well covered.

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

Conciseness4/5

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

Three sentences with high information density and no filler. The structure front-loads the purpose and then details filters, pagination, and output behavior. The parenthetical 'application source, metadata only' is slightly awkward but not wasteful.

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?

Given 7 optional parameters, no output schema, and no annotations, the description covers the main filter dimensions, pagination, and the summary/full-detail boundary. It could be more explicit about AND-combination semantics and output summary fields, but it is sufficiently complete for an agent to invoke it correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining filter semantics (module examples, type letters, layer options, titled meaning) and pagination usage, enriching the schema's parameter descriptions without repeating them verbatim.

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 browses and filters Ross ERP 8.0 programs, identifies the resource (programs) and scope (metadata only), and distinguishes itself by noting that lookup_program provides full detail. This goes beyond the tool name and separates it from related listing/search siblings.

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 recommends lookup_program when full detail is needed and describes the listing/filtering purpose. It does not explicitly mention when not to use the tool relative to search_programs or other siblings, but the filter-focused language and summary/detail pointer give strong usage context.

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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