recall

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

With no annotations, the description fully covers behavioral traits: hybrid search, scoping to type='note', relevance ranking, snippet-truncated output, and the need to call get_memory for full records. No contradictions.

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 concise with three sentences, front-loaded with the primary purpose. Every sentence adds value without fluff.

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 complexity and presence of an output schema, the description adequately covers the tool's behavior, output format (snippet-truncated), and relationship to siblings. It provides sufficient context for correct invocation.

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 description does not explicitly explain the individual parameters (query, limit, domain). While the purpose implies query is the search term, limit and domain are left unspecified. With 0% schema coverage, the description should compensate, but it largely omits parameter details.

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: recalling long-term knowledge saved with note(). It specifies the scope (type='note'), the search method (hybrid BM25 + vectors), and explicitly differentiates from sibling tools like search and get_memory.

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 explicitly provides guidelines on when to use this tool ('dedicated verb for bring back what I noted'), contrasts with search(type='note') as an alternative, and explains the recency behavior difference from checkpoints with pulse().

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