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

Annotations already declare the tool as read-only, idempotent, and non-destructive, lowering the burden. The description adds value by specifying exactly what counters are included (verification rate, confidence, source count, urgency, actionability breakdowns), giving the agent a clear picture of the response content beyond the annotations.

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 a single sentence with no filler words, front-loading the core action ('Return firehose/demo counters') and listing all relevant output metrics. Every word 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?

The tool is relatively simple with only two optional parameters and an output schema present, so the description does not need to explain return values. The key context—what kind of stats are returned—is provided, and the schema covers parameter details.

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%, and the schema itself provides a detailed explanation of agent_id including the first-call behavior. The description does not add any extra parameter guidance, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Return') and resource ('firehose/demo counters for recent agent-news events'), and enumerates the exact metrics returned (counts, verification rate, etc.). This clearly distinguishes it from sibling tools like tat_get_event, which likely retrieves a single event rather than aggregate statistics.

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 implies usage for obtaining aggregate statistics on agent-news events, but it does not explicitly state when to use this tool over alternatives or mention exclusions. For example, it could have said 'Use this for summary statistics; use tat_get_event for individual event details.' Without such guidance, the usage context is only implied.

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