smart_recall

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

No annotations provided, so description is fully responsible. It discloses fallback behavior (defaults to remember_context keys if no semantic match) and gives a threshold parameter for similarity. Does not mention side effects, but as a read-only retrieval, this is adequate.

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?

Two clear sentences plus an illustrative example. No wasted words. Front-loaded with the core functionality and an immediate example.

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?

While there is no output schema, the description implies the return value (cached context matching query). It explains the fallback mechanism and threshold. For a retrieval tool, this provides sufficient context for the agent to understand behavior.

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?

Input schema has 100% coverage with descriptions for all three parameters. Description adds value by explaining the overall purpose and example, but does not provide additional semantic detail beyond what the schema already offers. Baseline 3 is appropriate.

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?

Description clearly states it semantically searches cached context using natural language, distinct from exact key matching. Provides a concrete example (smart_recall('how does authentication work') returns auth architecture summary). Clearly differentiates from sibling tools like recall_context which likely do exact matching.

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?

Describes usage for semantic search where exact key matching is insufficient, with a natural language query example. Mentions fallback to remember_context keys if no semantic match, implying when exact matching might be needed. No explicit when-not to use or direct alternatives, but context implies differentiation.

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