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

With no annotations, the description must carry behavioral disclosure, and it does add one meaningful trait: the data is historical and not a live stream. However, it says nothing about data freshness, source scope, pagination, latency, or side effects, so behavioral coverage is only partial.

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?

The description is two short sentences with no filler. The core distinction is front-loaded, and the routing note immediately follows; every sentence 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?

Given full schema coverage, an output schema, and only one required parameter, the description supplies the key contextual information needed to choose and call the tool. It could add more detail about the historical time window or data sources, but nothing essential for a correct invocation is missing.

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 100%, so the parameters (entity, limit, platform) are already fully documented. The description only reinforces that the entity is the subject; it adds no extra meaning beyond the schema.

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 specific resource and state: 'Historical mention snapshot for an entity,' and explicitly distinguishes it from 'a live firehose.' It also names sibling tools for current discussion, making the tool's purpose and scope clear.

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 gives a direct routing rule: 'For current discussion, use community_signal / hn_attitude.' This tells the agent when not to use this tool and which alternatives to pick, while the historical framing implies when it should be used.

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