radmail_learning_insights

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

No annotations exist, so the description must disclose behavioral traits. It claims 'Transparency, not a black box' but fails to explicitly state side effects, whether it modifies data, or any authorization needs. For an informational tool, it should assert read-only nature.

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 two sentences, concise and front-loaded with the core purpose. It could be structured more formally, but it is efficient and avoids waste.

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?

For a tool with 2 optional parameters and no output schema, the description covers the gist but lacks detail on return values or behavior. Terms like 'learned response shape' are undefined, leaving ambiguity despite the low complexity.

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 50% (only includeBacklog has a description). The description adds no parameter-level details. With 2 parameters and no enums, the description should at least mention agentId's purpose to compensate, but it does not.

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 what the tool does: show insights RadMail has learned about the user, including specific categories like most-used tools, learned response shape, recurring focus, and capability wishlist. It distinguishes from siblings by focusing on learned patterns rather than current state or why something surfaced.

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?

No guidance is provided on when to use this tool versus alternatives like 'why_surfaced' or 'list_right_now'. The description implies usage for transparency, but there is no explicit when/why-not or mention of prerequisites.

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