update_datasources

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

No annotations are provided, so the description carries the full burden. It explains the shallow-merge behavior and that the Redux list is refetched at the end. It lacks details on error handling, idempotency, or limits, but the key behaviors are disclosed.

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 concise with four sentences, front-loaded with the primary purpose. Every sentence adds value, and there is no fluff.

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?

No output schema is provided, and the description does not explain the return value (e.g., success/failure, updated IDs). It also omits constraints like the maximum number of updates per call. For a tool with one parameter and good behavioral details, it is mostly complete but leaves some gaps.

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?

The input schema has 0% description coverage, so the description must compensate. It does so by detailing the structure of the 'updates' array entries: requiring 'datasource_id' and optional 'name' and 'datasource_config', and explaining how 'datasource_config' is shallow-merged. This adds significant meaning beyond the 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 tool updates multiple datasources in one call, specifying the structure of each entry and the shallow-merge behavior. It distinguishes itself from create_datasources and delete_datasources by focusing on updates.

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 implicitly conveys when to use this tool (updating multiple datasources at once), but it does not explicitly state when not to use it or provide alternatives like updating one-by-one. However, the context is clear enough for an AI agent.

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