Infer persona from memory

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false), the description discloses that inferred facts have lower confidence, never override explicit facts, and details two execution paths based on LLM configuration.

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 two sentences. The first sentence states the core action and differentiation; the second explains the two modes and confidence behavior. No extraneous information.

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 simple tool (zero parameters, no output schema), the description covers all necessary aspects: purpose, execution modes, confidence behavior, and return value. It is complete for the agent to understand 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?

There are no parameters, so schema coverage is 100%. The description appropriately adds no parameter details, but it does describe the return value and execution paths, providing value beyond the schema.

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: to derive persona facts from existing memories. It distinguishes from sibling tools like mindmap_persona_set by noting that inferred facts have lower confidence and do not override explicit settings.

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 explains when to use the tool (to infer persona facts) and outlines two execution paths (LLM-rich vs keyword heuristic). It could be more explicit about when not to use or suggest alternatives, but the differentiation from explicit setting is clear.

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