contact_stats

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the agent knows this is a safe, non-destructive read operation with limited scope. The description adds context about the type of analytics provided (message volumes, response times, patterns, trends) but doesn't disclose additional behavioral traits like performance characteristics, data freshness, or authentication requirements beyond what annotations provide.

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 - a single sentence that efficiently communicates the tool's purpose and scope. Every word earns its place, with no redundant information or unnecessary elaboration.

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?

For a read-only analytics tool with good annotation coverage but no output schema, the description provides adequate but minimal context. It states what analytics are available but doesn't explain the return format, data granularity, or how the analytics relate to the date parameters. The combination of annotations + description gives basic understanding but leaves questions about output structure.

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?

With 100% schema description coverage, the input schema already documents all three parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it mentions analytics types but doesn't explain how parameters affect those analytics or provide usage examples.

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 performs 'Deep per-contact analytics' and lists specific metrics (message volumes, response time estimates, conversation patterns, yearly trends), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'message_stats' or 'temporal_heatmap' which might offer overlapping functionality.

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 no guidance on when to use this tool versus alternatives. With many sibling tools offering related analytics (message_stats, temporal_heatmap, yearly_wrapped, etc.), there's no indication of what distinguishes this contact-focused analytics tool from other statistical tools in the server.

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