memory_extract

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

The description explains behavioral traits beyond annotations: store=true causes writes, store=false is read-only. It adds context about Japanese language analysis. No contradiction with annotations (idempotent, not read-only, not destructive).

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 reasonably concise, covering purpose, usage, parameter behavior, and sibling differentiation in a single paragraph. It could be more structured but is not excessively long.

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 description covers behavioral aspects and parameter semantics well, but lacks information about the output format of extracted facts. No output schema is provided, so the agent must infer the return structure. With moderate complexity, this gap reduces completeness.

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 100% with clear descriptions. The description adds value by explaining the behavioral difference of the 'store' parameter and the optional 'context_hint' usage, enhancing the schema information.

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 extracts facts (subject-predicate-object triples) from text, with specific verb 'extract' and resource 'facts'. It distinguishes from sibling memory_store by contrasting episode storage vs fact extraction.

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 explicit guidance on when to use store=true vs store=false, and contrasts memory_extract with memory_store. It implies usage context (Japanese text analysis) but doesn't explicitly state when not to use it or list alternative tools.

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