Query CAP sample data (CSV mock)

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds operational context (CSV files, CAP conventions, filter syntax) but does not disclose error behavior, pagination details beyond limits, or what happens if the entity is not found. Given the annotation coverage, this 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 plus a concise example, with the core purpose front-loaded and no redundant filler. Every sentence earns its place—first establishes the resource, then enumerates capabilities, and finally gives a concrete filter example.

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?

For a 7-parameter tool with an output schema, the description covers the essential query capabilities and the filter syntax. It does not explain the output shape, but the output schema handles that. Missing details like default behavior when projectPath is omitted are present in the schema. Overall, it's complete enough for successful invocation.

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%, so the schema documents all parameters. The description adds valuable syntax guidance for the filter parameter ('and/or, eq/ne/gt/ge/lt/le, contains' and an example), which is essential for constructing valid queries. It also clarifies that the data follows CAP conventions, which helps set expectations for projectPath and entityName.

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 a specific verb ('Executes a CQN-like query') and a specific resource ('CAP sample data (CSV files in db/data following CAP conventions)'). It lists the supported operations (projection, filter, order, skip/limit) and distinguishes this tool from siblings like query_odata_data by explicitly targeting local CSV mock data.

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 provides clear context that this tool is for querying CAP sample CSV data, which implies usage for local/testing scenarios. It does not explicitly mention when not to use it (e.g., against OData services) or name alternatives, but the context is strong enough for an agent to infer the primary use case.

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