get_listening_topic_metrics

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It describes the action as 'get metrics' (implying read-only) and gives metric examples, but does not mention side effects, permissions, pagination behavior, rate limits, or response format. This is insufficient for a tool with no annotation safety net.

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 extremely concise with two sentences. The first sentence states the core purpose with examples, and the second gives a key usage tip. No superfluous words; 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?

Although the description covers purpose and a prerequisite, it lacks completeness for a tool with 4 parameters and no output schema. It does not explain optional parameters (filters, page), how pagination works, or what the response contains. This leaves the agent with gaps for proper invocation.

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 baseline is 3. The description adds value by providing specific metric examples (volume, sentiment, engagement) beyond the schema's generic 'refer to docs' for the metrics parameter, and it clarifies the topic_id source via get_topics. This elevates the score above baseline.

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 clearly states the tool retrieves metrics (volume, sentiment, engagement) for a specific listening topic. It distinguishes itself from sibling tools like get_listening_topic_messages (messages) and get_topics (listing topics) by specifying 'metrics' and directing users to get_topics for IDs.

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 provides a clear prerequisite by advising to use get_topics first to obtain topic IDs. However, it lacks explicit when-not-to-use instructions or alternatives, though the context from siblings helps. This qualifies as 'clear context, no exclusions'.

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