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

The description adds valuable behavioral context beyond annotations: it states the tool is 'Deterministic fetch, no LLM cost' and 'Requires AUTARIO_API_KEY.' This complements the annotations (idempotentHint=true, readOnlyHint=false) without contradiction. The agent learns about side-effect freedom and authentication needs.

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 (4 sentences) with no redundant information. It front-loads the action and purpose, then adds usage conditions, return value, and authentication. Every sentence earns its place.

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?

Despite no output schema, the description explicitly states return values: 'Returns the new row count and the dataset_id you can then read with query_dataset / get_dataset_schema.' Combined with clear purpose, prerequisites, and behavioral notes, the description is fully complete for a single-parameter tool.

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 coverage is 100% with one parameter (connector_id) described as 'The id of the connector instance to refresh (from list_connectors).' The description adds no additional meaning beyond the schema; it only repeats 'connector' in a broader context. Baseline of 3 is appropriate.

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's purpose: 'Pull the latest data from a connector's source REST API now and refresh its hosted Postgres table on Autario.' It specifies the verb (refresh), resource (connector), and outcome (new rows, dataset_id). This distinguishes it from sibling tools like list_connectors (list only) and query_dataset (read only).

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 says 'Use when the user wants fresh data before analysis' and provides a prerequisite: 'The connector must already exist (the owner sets it up in the UI).' It does not explicitly state when not to use it or mention alternative tools, but the context is clear enough for an agent.

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