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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing the return envelope (total/count/offset/items/has_more/next_offset), which reveals pagination behavior, plus the promise that figures match the Idea Launch app. It says nothing about rate limits or ordering, keeping this below a 5.

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?

Purpose and the run-id use case are front-loaded in the first two short paragraphs, and the return shape is compact. The final sentence restates CTR and signups already listed in the opening line, a small redundancy that keeps it from a 5.

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 output schema, the description usefully supplies the return envelope, which covers the main complexity for an agent. However, the pagination and format parameters remain unexplained, so an agent has no guidance on how to page through results or which response_format to request.

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 description coverage is 0% for all four parameters, so the description carries the full burden, and it explains none of them. ideaId, limit, offset, and the markdown/json enum are never mentioned; the return-shape listing only hints that offset/limit exist. This is a clear gap against the low-coverage rule.

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?

States a specific verb and resource ('List every Ad Run for an idea') and enumerates the fields surfaced (status, platform, market read, CTR, signups). It clearly reads as a collection endpoint, distinguishable from the sibling get_ad_run, though it never names that sibling to sharpen the contrast.

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?

'Use this to see the history of experiments on an idea, or to find a run id' gives concrete use cases. It stops short of exclusions or alternatives (e.g. use get_ad_run when you already have a run id), so it is clear context without routing.

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