Recall

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

Annotations already indicate readOnlyHint=true and openWorldHint=false. The description adds context by specifying that output includes exact stored text, provenance, timestamps, and score components, and that no LLM rewrites are generated. This provides useful behavioral details beyond the annotations, though it omits information about rate limits or auth requirements.

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 paragraph that front-loads the core purpose, then details returns and key parameters. It is reasonably concise, though the structure could be improved by using bullet points or explicit sections. Every sentence contributes value.

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 11 parameters, 1 required, presence of output schema, and clear annotations, the description covers the main purpose, behavioral traits, and two important parameters. It explains historical query usage and hybrid mode. However, it does not address all parameters, which limits completeness for a complex tool. Still, it is adequate for basic usage.

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?

With 0% schema description coverage, the description explains two key parameters (hybrid, as_of) but leaves others unaddressed. The explanation of hybrid's utility for exact identifiers adds meaning beyond the schema, but many parameters (e.g., kind, fusion, namespace) remain undocumented in the description. The description partially compensates but is insufficient for full parameter understanding.

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 retrieves relevant memories with deterministic, source-traceable evidence, which is a specific verb+resource. It emphasizes no LLM rewrites, distinguishing it from other memory tools that may use generative capabilities. The purpose is unambiguous and well-articulated.

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 guidance for using hybrid mode with exact identifiers and explains the as_of parameter for historical queries. However, it does not explicitly contrast with sibling tools like inspect_memory or capture, nor does it state when not to use this tool. The guidance is present but incomplete.

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