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

With no annotations provided, the description carries the behavioral disclosure burden and does so well: it reveals that the tool catalogs and routes rather than synthesizes, takes no position on the arguments, and returns time-sensitive, dated rows. The warning that rows older than six months need a refresh is a valuable behavioral trait beyond the schema. It clearly implies a read-only, non-destructive list operation with no contradiction.

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?

Three sentences, each earning its place: the first defines the resource and its payload, the second frames what kind of artifact the tool returns, and the third warns about data freshness. It is dense but not bloated, and it never repeats schema details mechanically.

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 no-output-schema list tool with three optional enum filters, the description is nearly complete: it states what each returned item contains, what kind of data it is, and how quickly that data decays. It does not explicitly explain how the optional filters combine, but the schema's field descriptions make the filter semantics largely self-explanatory. An agent can reasonably decide when to call this tool and what to expect back.

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?

Stage and market parameters are already well documented in the input schema, and the description reinforces them by mentioning 'the markets it lands in' and 'its stage.' Category remains the weak point: it has no schema description and the tool description never explains how category divides the 37 conversations, despite six enum values. With schema coverage at 67%, the description adds some context but does not fully compensate for category's lack of meaning.

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 opens with a concrete referent — 'The 37 conversations currently moving the games industry' — and enumerates what each item contains: what it is, why it matters, markets, stage, and dated further reading. The 'routing map rather than a synthesis' phrase also differentiates it from summary/landscape-style sibling tools, and 'takes no position on any of them' clarifies its non-analytical role.

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 gives clear context for when this tool is appropriate: it is a 'routing map rather than a synthesis,' so an agent should use it to locate and route to ongoing arguments, not to get a synthesized position. The explicit freshness caveat — 'fastest-decaying data here' and 'anything older than about six months needs a refresh' — provides an actionable boundary for when results may be too stale. It does not name sibling tools as alternatives, so it stops short of a 5.

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