Idea statistics

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds the categories of computed output, but since an output schema exists, much of that restates structured data rather than adding new behavioral context such as freshness, live-vs-cached computation, or cost.

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?

A single sentence that front-loads the verb and lists the returned aggregates with zero filler. Every clause carries information about what the caller gets.

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 zero-parameter read-only aggregate tool with an output schema defining the return shape, the description covers what is needed to call it correctly. The only omission is guidance on when to choose it over list_ideas/search_ideas, which is a minor gap.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-parameter tool is 4. The schema confirms an empty argument object, so no gap exists.

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 states a specific verb ('Return') and resource, and enumerates exactly what is computed: total ideas, counts by domain, counts by status, and most-used tags. That aggregate nature inherently separates it from siblings like get_idea and list_ideas, but it never names or contrasts those siblings explicitly, so it stops short of a 5.

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?

Usage is only implied: an agent can infer this is for summarized/aggregate views rather than enumerating ideas, but the description gives no explicit when-to-use, no statement of when list_ideas or search_ideas is preferable, and no note on whether filters apply.

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