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

Beyond the readOnlyHint/openWorldHint annotations, it discloses exactly the surprises an agent would otherwise trip on: a 50-bucket cap, page/page_size having no effect on counts, and sort being validated but not affecting bucket order. These are non-obvious behavioral constraints that annotations cannot express.

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?

Four short sentences, front-loaded with the outcome (buckets + counts + cap) before the qualifiers. Only the 'facet accepts only app_id' clause duplicates the schema, a minor redundancy.

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 an output schema present, return values need no explanation, and annotations cover the safety profile; the description fills in the aggregation quirks and the sibling routing. It could say slightly more about whether the app_id/q filters scope the bucket set itself, which is the one remaining ambiguity.

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 100%, so the schema already documents all six parameters and the baseline would be 3. The description goes further by explaining that page and page_size are inert for counts and that sort does not reorder buckets, which tells the agent not to waste effort tuning those inputs; the facet enum restatement is redundant.

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: return app-id facet buckets with counts for the Steam news dataset, capped at 50. It is clearly distinct from datasets_steam_news_search, which it names as the record-level alternative, though the term 'facet buckets' still assumes the reader knows what an aggregation bucket is.

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?

It establishes context ('honoring the app_id filter from datasets_steam_news_search') and routes record lookups to datasets_steam_news_search explicitly. What it lacks is an explicit negative case (e.g., do not use this when you want the news rows themselves), so the boundary is clear but not stated as a rule.

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