Overview of the Ross ERP 8.0 application layer — the client menu tree of UI facilities (screens, reports, inquiries, maintenance functions): total facilities, and their breakdown by system (e.g. ACCOUNTS_PAYABLE), database (FIN/MAN) and class (REPORT, MAINTENANCE, INQUIRY, ...). Use this first to orient before browsing facilities.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently describes the output as an overview with totals and breakdowns, making it clear this is a read-only, non-mutating operation. It does not mention potential limitations like performance or access restrictions, but for a simple stats tool, the information provided is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose, and every phrase adds value. It includes concrete examples (ACCOUNTS_PAYABLE, FIN/MAN, REPORT/MAINTENANCE) without unnecessary padding, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and no annotations, the description is complete. It explains what the overview contains, how it's grouped, and provides usage guidance. Nothing critical is missing for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% coverage, so the baseline is 4. The description adds meaningful context about what the tool returns and how it groups facilities (by system, database, class), which is more than just restating the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: it provides an overview of the Ross ERP 8.0 application layer with total facility counts and breakdowns by system, database, and class. This specific, detailed description distinguishes it from sibling tools like list_facilities or search_facilities, which focus on listing or searching rather than aggregate statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this first to orient before browsing facilities,' providing a clear when-to-use guideline. It does not explicitly name alternative tools or specify when not to use it, but the directive to use it first is sufficient guidance for a parameterless overview tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.