brain_diff

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

No annotations exist, so the description carries full burden. It discloses the output structure (four categories of changes) and gives an example output. It implies no destructive side effects but does not explicitly state that it is read-only or discuss error scenarios.

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 a single, well-organized paragraph. It front-loads the core purpose and analogy, then lists output categories, a use case, and an example. Every sentence adds value without redundancy.

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 no output schema, the description adequately explains return types (structured changelog with four categories) and provides an example snippet. It does not cover error conditions or edge cases, but for a diff tool with clear input, it is sufficiently 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?

Input schema has 100% coverage with clear descriptions for all three parameters. The description adds value by demonstrating parameter usage in an example ('since='7d'') and tying them to real-world use, though the schema already provides sufficient detail.

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 uses a clear analogy ('git log for your AI Brain') and specifies the resource ('AI Brain') and action ('see exactly what changed'). It enumerates the four types of changes (new, updated, recalled, decayed), making it distinct from siblings like brain_search or brain_predict.

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?

Explicitly gives a use case: 'Perfect for weekly reviews' and provides an example call with expected output. It does not explicitly contrast with alternatives, but the unique purpose (changelog) implicitly distinguishes it from other brain_* tools.

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