chat_analytics

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only reveals that the tool reads cached messages. It does not state whether cache staleness matters, whether an explicit sync is required first, whether results are sorted, or any side effects. This is a thin behavioral contract 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 a single, focused sentence that front-loads the core purpose and result. It wastes no words, though it could benefit from a brief note on caching behavior or output ordering without losing conciseness.

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 has no output schema and no annotations, leaving the description as the sole source of contextual information. It does not explain what the return value looks like (e.g., array of senders with counts, sorted descending), the role of the optional parameters beyond their schema defaults, or how cache freshness affects results. For a completly optional-parameter analytics tool, this is insufficient.

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 all four parameters are already documented in the schema. The description adds minimal semantic value beyond naming the output ('top senders by message count'), which weakly ties to the limit parameter. Baseline 3 applies here.

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 ('Get'), states the resource ('cached messages'), and specifies a concrete output ('top senders by message count'). It is clearly distinguishable from most siblings, though it does not explicitly differentiate itself from get_dialogs_stats, which could also provide chat analytics.

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?

Usage context is implied through 'from cached messages'—an agent can infer this tool should be used when analytics from cached data are desired. However, there is no explicit mention of alternatives (e.g., get_dialogs_stats) or when not to use this tool, leaving the routing partially to inference.

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