brain_set_pref

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

With no annotations provided, the description carries the full burden. It discloses that preferences are stored in Redis and survive restarts, which is adequate for a simple set operation. However, it does not mention overwrite behavior, error conditions, or whether the operation is synchronous.

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 three short sentences, front-loaded with the core purpose. Every sentence adds value—purpose, storage, and a concrete example. No wasted words.

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 the tool's simplicity (3 parameters, no output schema), the description is mostly complete. It covers the purpose, storage, and a known key. It could briefly mention the return value (e.g., success indicator) but is not critically missing information.

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 100%, so the baseline is 3. The description adds minimal value beyond the schema by explaining the concept of 'user preference' and providing context for the auto_changelog key, but it does not introduce new constraints or format details.

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 verb 'persist' and resource 'user preference' for a Brain instance. It distinguishes from siblings like brain_get_pref (get) and cache_set (generic cache) by specifying that it's a user preference and giving a concrete example (auto_changelog).

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 implies usage for setting persistent user preferences with examples, but it does not explicitly state when to use this tool versus alternatives (e.g., brain_get_pref, cache_set) or provide exclusions. The context is clear but not directive.

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