get_conversations_summary

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

With no annotations, the description carries full burden. It mentions the output is a statistical summary, but does not disclose if it is read-only, any side effects, rate limits, or response structure. The agent cannot infer safety or cost of invocation.

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 very short (two phrases) with no fluff. It is efficiently structured but slightly fragmented. Every word earns its place, though it could be better organized.

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 the complexity (13 parameters, no output schema, many siblings), the description is insufficient. It does not explain how the summary is computed, the meaning of urgency, or how period interacts with date_from/date_to. The agent lacks information to use the tool effectively.

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% but parameter descriptions are basic (e.g., 'Texto de busqueda' for query). The tool description adds no additional meaning beyond the schema. Baseline 3 is appropriate as the schema already documents parameters, despite lack of enriched context.

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 it provides a statistical summary of conversations for a period, listing example metrics (total, average satisfaction, urgency). It distinguishes itself from sibling tools like search_conversations or get_conversation_detail by focusing on 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 the tool is for obtaining period-based summaries, but it does not explicitly state when to use it versus alternatives (e.g., search_conversations for searching, get_conversation_analytics for detailed analytics). No exclusions or when-not-to-use guidance is provided.

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