maltego_reset_learning

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

The description adds behavioral context beyond annotations: it clarifies that both in-memory and on-disk stores are cleared, and that the operation is a no-op when learning is disabled. Annotations already indicate destructiveness and idempotence, so the description complements them well.

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 very concise, consisting of three short sentences. It is front-loaded with the main action, followed by edge-case behavior and a return type. No unnecessary words.

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?

With no parameters and an output schema that indicates a simple confirmation string, the description is complete. It covers the main purpose, edge case, and return type, leaving no ambiguity for a simple reset action.

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 provides no parameter information, which is appropriate as there are none. Baseline 4 is suitable.

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 clears the cross-investigation learning store, both in-memory and on disk, and is a no-op when learning is disabled. This is a specific verb-resource combination that distinguishes it from siblings like maltego_learning_stats.

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 mentions when it's a no-op (learning disabled) but does not provide explicit guidance on when to use it vs. alternatives, such as when learning stats are unnecessary or when a reset is needed. Usage context is implied rather than explicit.

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