gaps

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context about the internal mechanism ('substrate logs every recall...') and the nature of the output (frequently-asked, poorly-answered queries), which enhances transparency beyond what annotations provide.

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 reasonably concise, starting with the core purpose and then elaborating. It uses a bullet-like list for parameters. One minor point: the first sentence could be slightly more front-loaded, but overall it is efficient and well-structured.

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?

The tool has three parameters with defaults and an output schema. The description explains the tool's functionality, internal logging mechanism, and intended use case for proactive learning, which is fully adequate given the output schema provides return value details.

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 0%, but the description compensates by explaining each parameter's semantics: min_count surfaces queries asked at least N times, max_avg_top_score filters by average best recall score, and limit caps results. This adds essential meaning beyond the schema's type and default values.

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 purpose as 'Surface knowledge gaps — frequently-asked, poorly-answered queries'. This is a specific verb-resource combination that distinguishes it from siblings like 'recall' and 'memory' which deal with storing or retrieving specific facts, while this tool identifies unknown areas.

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 provides clear usage context: 'Use this to drive proactive learning: when the agent sees a gap, it can ask the user, fetch info, or note the limitation.' However, it does not explicitly exclude cases where this tool should not be used or mention alternative sibling tools such as 'stats' for similar analysis.

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