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

Annotations already carry safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false) and openWorldHint=true. The description adds genuinely useful behavioral context beyond that: the >=2 distinct authors constraint and the exclusion of copypasta/near-identical posts from one account. This meaningfully shapes what an agent should expect in the result set.

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?

Two sentences with no filler. The defining scope ('raw clusters... without the prose') is front-loaded, and the critical data-quality filter (copypasta exclusion) is the only secondary detail. Every clause earns its place.

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 one-optional-parameter, read-only tool with safety covered by annotations, the description is nearly complete: it defines the data semantics and the inclusion/exclusion rule. The only gaps are explainability of 'limit' and the absence of any return-shape hint, which is softened by having no output schema to reference.

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%, so the description must compensate, but it never mentions the single 'limit' parameter — how it bounds results, whether it truncates, or how clustering count relates to it. While the name/default make it partly self-evident, the description adds zero parameter-level 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?

States a specific verb+resource ('raw clusters behind the stories') and an explicit consumer ('for a model doing its own summarisation'). The phrase 'without the prose' differentiates it from prose-returning siblings like get_story_posts and get_trending_stories, so an agent can pick it without opening schemas.

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 a clear intended context — raw cluster data for a model that will do its own summarisation — which implies when to choose this over prose-bearing siblings. It stops short of explicitly naming alternatives or stating when-not-to-use, leaving the sibling routing slightly implicit.

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