update_preferences

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It indicates mutation and mentions api_key fallback, but does not disclose whether the provided preferences replace the entire user preference set or are merged, whether unspecified preferences are cleared, or what side effects occur. This is a significant gap for a mutation tool.

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 compact and well-structured: a one-sentence purpose followed by an Args section. No fluff, but it could earn a 5 with a clearer behavior note or example.

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?

Given that output schema exists, return values are covered, but the description misses crucial behavioral context: whether the update is additive or destructive, what happens to existing preferences not in the dictionary, and what counts as a valid preference. An agent could easily call this incorrectly and unknowingly wipe preferences. The api_key fallback is useful, but the missing overwrite semantics make this incomplete for a mutation 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 description coverage is 0%, so the description must compensate. It does: 'preferences' is explained as a dictionary of preference keys and new values, and 'api_key' is explained with its environment-variable fallback. This adds meaningful semantics for both parameters, though it lacks detail about valid preference keys or value types.

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 (update) and resource (user preferences) in a Mess portal, clearly distinguishing it from read-oriented sibling tools like get_preferences. The phrase 'all user preferences' is slightly ambiguous as to whether it means a full replacement or a blanket update, but the core purpose is clear.

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?

No guidance is provided about when to use this tool versus alternatives, such as when a partial update is appropriate or whether to prefer get_preferences first. The description only states what the tool does, not the conditions under which it should be chosen or avoided.

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