set_result_set_caching

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

With no annotations, the description carries full burden. It discloses the exact SQL executed (ALTER DATABASE...), that it returns effective settings after change, and that it rejects unsupported endpoints with ToolError. This is adequate, though it does not discuss idempotency or side effects.

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 well-structured with a clear verb-resource statement, followed by SQL command details, then constraints, then an Args list. Every sentence adds value, and there is no extraneous text.

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 that an output schema exists, the description need not detail return values, but it notes 'returns the effective settings read back'. Parameters are fully covered, and usage constraints are explicit. The tool is complete for its purpose.

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 0%, but the description provides an Args section that explains each parameter: workspace (name or GUID), item (name or GUID, with note about SQL Analytics Endpoints), and enabled (True/False). This adds significant meaning beyond the raw 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 the verb 'Enable or disable' and the resource 'result-set caching on a warehouse'. It is specific and distinct from sibling tools like set_time_travel_retention or set_workspace_collation, which manage different settings.

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 states that the tool is only supported on Fabric Data Warehouses, not SQL Analytics Endpoints, and that unsupported endpoints will raise a ToolError. This provides clear when-to-use and when-not-to-use guidance, though it does not mention alternative caching mechanisms.

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