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Ross ERP Data Dictionary

program_stats

Overview of the Ross ERP 8.0 program catalog — every application-source program (metadata only, no source body): total programs, how many declare a TITLE id, how many carry Data Dictionary table links, total program→table edges, read/write counts (withWrites programs, writeEdges program→table write edges), base vs vendor-core split, program→program call-graph counts (programs with outbound calls, total call edges) and how many back a menu facility, plus the module and type breakdowns. Use this first to orient before browsing programs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 full burden and does well by noting 'metadata only, no source body' and detailing exactly what counts are provided. It implies read-only behavior but does not explicitly state 'no side effects' or mention auth/rate limits, which are not relevant here but could be more explicit.

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 dense sentence that front-loads the purpose and enumerates specific metrics. It is somewhat long but every clause adds information; it could be improved with bullet points, but it remains efficient and free of filler.

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?

For a stats tool with no parameters and no output schema, the description is quite complete: it lists all major metrics, the scope ('every application-source program'), and the intended first-use context. It does not specify the exact output format (e.g., JSON fields), but that is minor given the descriptive enumeration.

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?

The tool has zero parameters, so the baseline score is 4. The description correctly does not attempt to document parameters, and the schema already covers the empty parameter list fully.

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 it provides an 'Overview of the Ross ERP 8.0 program catalog' with a specific list of metrics (totals, TITLE id counts, table links, read/write counts, etc.). This distinguishes it from sibling tools like list_programs or lookup_program, which deal with individual programs or listings.

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?

The final line 'Use this first to orient before browsing programs' gives explicit guidance on when to use the tool. It does not explicitly name alternatives or provide when-not-to-use exclusions, but the context implies it precedes other browsing tools.

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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