list_tables

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

No annotations exist, so the description carries the transparency burden. It discloses a meaningful behavioral trait: 'Results are cached for 5 minutes.' The verb 'List' implies a read-only operation, but it doesn't describe output shape or pagination; still, the caching note adds useful context beyond the schema.

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?

Three concise sentences that are front-loaded with the core purpose and parameter usage, with no filler or redundant detail.

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 is a relatively simple listing operation, and all three parameters are documented in the schema. The description adds filtering guidance and caching behavior. It does not specify the return format, but given the simplicity and lack of output schema, the description is sufficiently complete for an agent to 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?

Input schema description coverage is 100%, and the description repeats the meaning of customOnly and nameContains already present in the schema. It does not add new parameter-level detail beyond the schema, so the baseline of 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 opens with 'List all available Dataverse tables (entities)', a specific verb+resource pair that clearly distinguishes this from sibling describe_table, which describes a single table. The mention of 'available' clarifies the tool returns the full set of tables.

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?

It provides actionable usage guidance by explicitly mentioning how to filter results: 'Use customOnly=true to see only custom tables. Use nameContains to search by name substring.' This gives clear context for invocation, though it does not explicitly name alternative sibling tools or state when not to use this tool.

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