test_datasource

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

No annotations provided, so description carries full burden. Only states 'Test connection' without disclosing behavioral traits such as whether it modifies anything, what happens on success/failure, or any side effects. For a test tool, likely read-only but not stated.

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?

Extremely concise: one sentence describing purpose plus a usage hint. No unnecessary words, perfectly 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?

Given only 1 parameter and no output schema, the description covers purpose and usage but lacks details on behavioral specifics (e.g., what 'test' entails, error handling). Adequate but could be more complete.

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%, and the parameter 'datasource_name' is already described as 'Name of the data source to test' in the schema. The description does not add any additional meaning beyond this, so baseline score 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?

Description clearly states 'Test connection to a data source' which is a specific verb+resource. It distinguishes from sibling tools like add_datasource, remove_datasource, list_datasources, etc., which have different purposes.

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 explicit usage scenarios: 'After adding a new data source, when user reports issues, or before starting reconciliation.' This gives clear context on when to use, though it doesn't explicitly list when not to use or alternative tools.

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