kernel_brain_stats

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

With no annotations, the description carries the full burden, and it does disclose the shape of what the tool reports (aggregate counts and watermarks), implying a non-mutating read. It does not state side-effect freedom, cost, freshness/staleness semantics of the watermarks, or whether it scans the whole store.

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?

A single compact sentence that front-loads the overall concept and then enumerates the three metric groups. It is efficiently sized, though it is a noun phrase lacking a verb, and 'unified space' / 'watermarks' are unexplained jargon.

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?

With zero parameters and an output schema present, the description only needs to orient the agent, which it does by naming the reported metrics. The remaining gap is conceptual — what 'unified space' and 'per-source watermarks' actually denote — rather than anything needed to 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The schema is trivially complete for an empty object.

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?

Names the specific metrics returned (total items, count per kind, per-source watermarks), which makes clear this is a coverage/statistics report. It does not, however, define what the 'unified space' is or distinguish itself from sibling stats tools like kernel_agents_stats or kernel_marketplace_stats.

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?

There is no when-to-use guidance at all — no statement of when an agent should call this rather than kernel_brain_recall, kernel_brain_index, or the other *_stats siblings. The description reads as a return-value label, not an instruction about invocation context.

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