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

Annotations already declare this is a non-readonly, non-idempotent, non-destructive write with open-world scope, so safety is covered. The description adds value beyond that by disclosing the return behavior ('Returns what it read') and pointing to a `say` field with a ready-to-read summary, which the agent would otherwise not know. It stops short of saying how partial or failed parses are reported.

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?

Three short sentences with zero padding: purpose first, then a concrete example, then return-value behavior. Every sentence earns its place and the core capability 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?

There is no output schema, so the description correctly compensates by explaining the return ('what it read') and the `say` summary field. For a one-parameter non-idempotent write, this is nearly complete; the only gap is any acknowledgment that re-running may overwrite or merge existing preferences.

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?

With a single parameter at 100% schema coverage, the schema already documents `text` as 'The person's own sentence.' The description's example adds a useful sense of the expected input shape, but no additional constraints (length, language, ambiguity handling) beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb and resource ('Set several preferences') and the distinctive input mode ('from one sentence'), which separates it from the sibling update_preferences. However, it never names that sibling or explicitly contrasts structured vs natural-language input, so differentiation is left partly to inference.

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 worked example ('data analyst in Leeds or Manchester, hybrid, over £30k, no crypto') implies when this tool is useful, namely free-form sentences rather than field-by-field updates. There is no explicit when-to-use guidance, no mention of update_preferences as the structured alternative, and no note on what happens if the sentence is ambiguous.

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