Conversation Stats

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds the aggregation granularity (daily, opened vs closed) but says nothing about defaults when the date range is omitted, timezone handling, or the shape/limits of the returned series.

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?

A single, front-loaded sentence that identifies the metric, the entity, and the temporal scope with zero filler. Nothing is redundant or padded.

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?

With no output schema, the description should clarify the returned structure and date-range defaults, but it only hints at 'daily counts.' It is adequate for a simple read tool but leaves the agent guessing about default ranges and response format.

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 organizationId (with a pointer to organization_list) and the two YYYY-MM-DD date fields are fully documented in the schema. The description's 'organization for a date range' only restates what the schema already provides, so baseline 3 applies.

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?

States a specific resource and metric ('daily counts of opened and closed conversations of an organization') with a clear scope ('for a date range'). It is distinguishable from conversation_list/thread, but it does not differentiate itself from close siblings like conversation_totals, conversation_metrics, or conversation_stats_by_member.

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?

No guidance on when to choose this over the many overlapping conversation-analytics siblings (conversation_totals, conversation_metrics, conversation_stats_by_member). Usage must be inferred purely from the noun phrase 'daily counts'.

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