query_odata_v4

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

With no annotations, the description carries the full burden. It discloses a critical behavioral trait: large tables (e.g., GLTran) will timeout without a filter, and advises always using $select to limit returned fields. This goes beyond the schema and provides valuable operational context, though it doesn't address error handling or response format.

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 five sentences, all informative and earning their place. It front-loads the core purpose, gives entity examples, and ends with critical usage warnings in clear format. No fluff or unnecessary repetition.

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?

The tool has 6 parameters, no output schema, and moderate complexity. The description covers purpose, entity discovery, and critical filtering guidance. It could mention error behavior or pagination details, but the schema covers parameters and the guidance is sufficient for most use cases.

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?

Schema description coverage is 100%, with parameter descriptions that include examples and formats (e.g., filter datetimeoffset, entity names). The description adds no new parameter semantics beyond emphasizing $select usage, so the baseline 3 applies.

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 the tool queries any Acumatica DAC table directly via OData v4, with a specific verb and resource. It lists example entities (SOOrder, BAccount, InventoryItem) and distinguishes itself from higher-level sibling tools by emphasizing raw DAC access.

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?

Provides actionable guidance: tells users to use list_odata_v4_entities to discover valid entity names, and warns to always apply filters and $select to avoid timeouts. However, it doesn't explicitly contrast with sibling tools like query_sales_orders, though the 'directly via OData v4' wording implies a low-level use case.

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