Ross ERP Data Dictionary

lookup_program

Full detail for one Ross ERP 8.0 program, by TITLE program-id (e.g. AP_A_002) or source basename (e.g. ap_a_check_register): its module, type, layer, declared title, internal PROCEDURE_FORM procedures, the Data Dictionary tables it references — each classified read vs read-write (a write is a FIND IN.../LOCK=WRITE update, an ADD, or a DELETE) with a writeCount — its call graph (the programs it invokes and the programs that invoke it, from PERFORM "GEM:"), the menu facilities it backs, and — for programs with no TITLE label — a display name carried from the menu facility's registry description. Metadata only — no source body.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Program id or basename, e.g. AP_A_002 or ap_a_check_register

TDQS

A4/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explicitly states 'Metadata only — no source body,' and defines write classification (FIND IN.../LOCK=WRITE, ADD, DELETE) and writeCount. It also explains fallback naming for programs without a TITLE label. This is detailed, though it doesn't explicitly address side effects or error behavior.

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?

The description is a single long sentence but structured with colons and em-dashes. It front-loads the core purpose ('Full detail for one Ross ERP 8.0 program') and then enumerates contents. While long, every item adds value; no filler or repetition.

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

Completeness5/5

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

For a tool with no output schema, the description thoroughly enumerates what will be returned: module, type, layer, title, procedures, table references with read/write classification and writeCount, call graph (both directions), menu facilities, and a fallback display name. It also clarifies the absence of source body. This is complete for a metadata lookup.

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?

The single parameter 'id' is already fully described in the schema ('Program id or basename, e.g. AP_A_002 or ap_a_check_register'). The description repeats these examples but adds no new semantic information beyond what the schema provides. Therefore baseline 3 applies.

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 begins with 'Full detail for one Ross ERP 8.0 program' and enumerates specific attributes (module, type, layer, procedures, table refs, call graph, menu facilities). This clearly distinguishes it from sibling lookup tools like lookup_facility and lookup_table.

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

Usage Guidelines3/5

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

The description implies usage by stating 'Full detail for one program' and giving input forms, but it does not explicitly contrast with sibling tools such as search_programs or program_stats. No 'when to use' or 'when not to use' guidance is provided.

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

All Ross ERP Data Dictionary tools Inspect

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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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