brain_recent_changes

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that output is in 'plain language' and focuses on changes over a period, which implies a read-only operation. However, it does not specify what types of changes are included (e.g., creations, edits, deletions) or the exact format of the response, leaving some ambiguity. This is adequate but not rich.

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 only two sentences long, with the purpose front-loaded in the first sentence and usage examples in the second. Every sentence earns its place, and there is no redundant or extraneous wording.

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 fairly complete. It explains the tool's purpose and gives concrete usage scenarios. However, it does not detail the return structure or edge cases (e.g., empty results), so it's not a perfect 5, but it is well-suited for an agent to select and invoke the 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 100%, so the schema already fully documents all three parameters. The description adds no additional parameter-specific information beyond what the schema provides. Baseline for high coverage is 3, and the description does not improve on that.

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 tool's function: 'What changed in the brain over a period, in plain language.' It uses a specific verb (changed) and resource (brain), and the mention of digests and work in progress differentiates it from sibling tools like search or get_thought. The purpose is immediately identifiable and distinguishes from alternatives.

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 gives explicit use cases: 'Call it for digests' and 'to understand what work was in progress before continuing it.' This provides clear context for when to use the tool. However, it does not mention when not to use it or name specific alternative tools, so it falls short of the highest bar.

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