get_user_preferences

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

No annotations are provided, so the description carries the behavioral burden. It clearly indicates this is a read operation via "Get" and states when it should or should not be invoked, which implies no mutation. It also discloses what data is returned, though it does not explicitly discuss side effects, permissions, or failure behavior.

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 longer than average but every part contributes: purpose, usage conditions, alternatives, category keys, and triggers. It front-loads the core purpose, then moves to when/how to use it. It is slightly dense but not wasteful.

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?

The tool has only one optional parameter and no output schema, so the description meaningfully fills the gap by listing returned data elements and call triggers. It does not describe response format or error cases, but for a straightforward preference getter with this rich usage guidance, it is reasonably 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?

The schema already documents the single parameter as "Preference category key" with 100% coverage, so the baseline is 3. The description adds value by listing the actual category keys (dairy, grocery, apparel, pets, beauty, household, pharmacy, gifts, kids, digital), which enriches semantics 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 opens with a specific verb and resource: "Get the user's category preferences". It enumerates concrete content (fat %, brands, sizes, pets, schema, learned signals, onboardingPurposes) and differentiates from siblings by naming list_purchases and search_products explicitly.

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?

Usage is strongly contextualized: "Call before search_products only when the owner already asked to buy or to look in AgentPay", "Do not fetch prefs for idle advice", and it gives explicit alternatives for related phrases: "For «как обычно», «то же самое», «прошлый раз» call list_purchases first."

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