Conversation Metrics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so safety and repeatability are covered. The description adds the aggregation scope (organization-wide, date range) and enumerates the returned metrics, which is useful return-value context given there is no output schema, but it discloses no auth, rate-limit, or default-range behavior.

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 dense sentence front-loads the scope before the colon and then lists outputs efficiently with no filler. The long enumeration of metrics is justified because no output schema exists, though the phrasing is noun-heavy rather than action-oriented.

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, enumerating the returned metrics is the right move and partially compensates. However, it omits whether dates are optional or defaulted, how metrics are segmented (per member vs. per organization), and how it relates to the several sibling statistics tools an agent could confuse it with.

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% and all three parameters are documented, including the YYYY-MM-DD format and the pointer to organization_list. The description only loosely ties startDate/endDate together with 'for a date range' and adds no syntax or default behavior beyond the schema.

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 names a clear resource (organization support metrics) and scope (date range) and enumerates the specific metrics returned. It never distinguishes itself from the numerous sibling statistics tools (conversation_stats, conversation_stats_by_member, conversation_totals, inbox_statistics), so an agent cannot tell which of the overlapping stats endpoints to pick.

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?

There is no when-to-use guidance, no statement of when to prefer this over conversation_stats, conversation_stats_by_member, or conversation_totals, and no note about date-range defaults or prerequisites. The reader must infer usage entirely from the metric list.

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