describe_datasource

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 accurately explains the default behavior (tables are included by default), the logic for list_tables, and the handling of schema_name including the edge case 'Ignored when list_tables=False.' This goes beyond the schema and gives the agent meaningful behavioral expectations.

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: a one-sentence summary, a one-sentence usage context, and a concise Args list. Every sentence adds necessary information, and the most important scoping detail (verify before ingest) is front-loaded.

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 describe tool with an output schema, the description covers all needed call context: what it returns at a high level, how to use it in the datasource workflow, and complete parameter semantics. The presence of an output schema lessens the need to document return values in prose, so nothing critical is missing.

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%, so the description must fully compensate for the bare parameter titles. It does: 'name' is sourced from list_datasources, 'list_tables' is explained with its default and effect, and 'schema_name' gets an example ('public'), its default behavior, and its interaction with list_tables. All three parameters are richly documented.

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 a specific verb and resource: 'Show datasource details: connection status, available schemas, and (by default) the tables.' It clearly distinguishes this from sibling tools like list_datasources and ingest_datasource_models by framing it as the verification/exploration step between them.

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 when to use the tool: 'Use this after create_datasource to verify the connection and explore what's queryable before calling ingest_datasource_models.' This gives an agent a clear workflow position and eliminates ambiguity about where this tool fits among siblings.

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