What matters in a brain — hubs, orphans, stale questions

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

With no annotations provided, the description carries the burden, and it does well by calling the operation a 'read' and explaining the meaning of the outputs ('load-bearing decisions', 'maybe forgotten', 'aging & unresolved'). It implies read-only behavior and gives interpretive context, though it does not state side effects or limitations explicitly.

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 front-loaded: the first sentence states what the tool reads and what it returns, and the second sentence explains when to use it. No wasted words, and the structure makes the tool easy to grok quickly.

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?

For a read-only inspection tool with three optional parameters and no output schema, the description is nearly complete: it covers outputs, purpose, and timing. It could be more complete by mentioning that this is a read-only operation more explicitly and by addressing how it differs from similar sibling tools, but the core context is sufficient.

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 parameters are already well documented. The description adds some context about 'stale open questions' and 'area sizes', which loosely relates to staleDays and view, but it does not meaningfully enrich the parameter semantics beyond what the schema already provides.

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 identifies a specific action ('Structural read of a brain.klypix') and enumerates concrete outputs: hub cards, orphaned decisions, stale open questions, and area sizes. It is easy to understand what the tool does, but it does not explicitly differentiate itself from sibling tools such as brain_lens or brain_connect.

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 usage contexts: answer 'what matters here / what am I forgetting / what should I review?' and use it at the start of a planning session or before tidying. It does not state when not to use the tool or name alternatives, so it stops short of a 5.

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