register_source

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

Even though annotations already include idempotentHint=true, the description adds essential behavioral nuance: 're-registration is a no-op if data is unchanged,' 'persists the source profile under the active API key's organization,' and 'After registration the source is queryable by name via query_data.' It also discloses the return shape (source_id and profiled schema with columns, roles, formulas, and join keys), which is especially valuable with no output schema present.

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 dense but efficient, front-loads the core purpose in the first sentence, and every subsequent clause adds value — lifecycle behavior, return values, and routing guidance. The 'Which to use' section could be seen as extra, but it directly supports correct tool selection and is not redundant. No filler or tautology exists.

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 tool with nested objects, no output schema, and multiple input formats, the description covers all essential call-driving information: what it does, how registration persists, idempotency, the exact return contents, how to query the registered source, and alternatives. Nothing critical is missing for an agent to decide whether and how to invoke it.

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 baseline is 3. The description does not add significant meaning to the source parameter beyond what the schema already says, although it restates 'Provide exactly one of: records, csv, json_str, url.' No additional parameter semantics are introduced, so the baseline 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 states a specific verb and resource: 'Register a data source' and immediately distinguishes it from alternatives by calling it 'the advanced path — full column profiling, formula detection, and join-key detection.' It explicitly contrasts with onboard_dataset and connect_data, making the tool's unique purpose in the sibling family unmistakable.

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 includes an explicit 'Which to use' section that names alternative tools and the conditions for choosing them: 'use onboard_dataset for semantic training, or connect_data for refreshable live connections.' It also specifies the follow-up action ('browse the results with list_data') and states the tool is for the advanced profiling-and-join path, leaving no ambiguity about when to select it.

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