recall_trace

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 well by disclosing what the tool returns: candidates scanned plus top results with scores and reasons. It does not mention side effects or permissions, but for an explanatory tool this is reasonably transparent about the core behavior.

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, front-loaded sentence with no fluff. Every phrase adds value, and it efficiently captures the tool's purpose and output components.

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 moderately complex tool with no output schema and no annotations, the description explains the purpose and output shape but leaves gaps: parameter meanings are not fully specified, and usage context relative to many sibling tools is only implicit. It is not a complete replacement for schema/annotation guidance.

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 coverage is 0%, so the description must compensate for both parameters. It implies the query parameter and mentions 'top results,' which loosely maps to top_k, but it does not explicitly define top_k, its default, or constraints. This leaves significant ambiguity for the integer parameter.

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 specific verb 'explain' and clearly identifies the resource ('why a query recalls what it recalls') plus the components of the explanation ('candidates scanned, top results with scores and reasons'). This distinguishes it from sibling tools like 'recall' or 'search' which return results rather than explain them.

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 implies usage for gaining a metacognitive explanation of a query's recall behavior, which is a clear context. However, it does not explicitly contrast with alternatives like 'recall' or 'retrieval_quality', nor does it state when not to use it, so it lacks explicit exclusions or named alternatives.

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