recall

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals important behaviors: memory ranking by relevance, hop=1 vs hop=2, and that 'Memories get stronger each time they're recalled.' This gives the agent a clear picture of side effects and retrieval semantics beyond the schema.

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 dense paragraph but every sentence contributes value—the imperative call order, the core purpose, parameter nuances, output mechanics, and memory strengthening effect. It is front-loaded with the most critical usage instruction.

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 four parameters and no annotations, but the description covers the key concepts: namespace, expansion, hop levels, and relevance ranking. An output schema exists, so return value details are not needed. Minor gaps include lack of mention of empty results or error behavior, but overall it is well-rounded.

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 schema has 0% description coverage, so the description must compensate. It explains namespace ('filters to a specific project/context'), expand ('returns up to 2x results'), and implies query semantics through 'search by concept.' top_k is not explicitly explained, but ranking by relevance with a default value makes it self-explanatory.

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 function: 'Search long-term memory by concept.' It explicitly instructs to call it first before every response, distinguishing it from sibling tools like remember or list_memories. The namespace and expand parameters are also described with specific behavior.

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?

Provides strong when-to-use guidance: 'CALL THIS FIRST before every first response' and suggests expand=True 'when initial results feel insufficient.' However, it does not explicitly mention when not to use it or name alternatives like list_memories or related, so it falls short of full alternative differentiation.

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