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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real context beyond them: it explicitly scopes the output to counts only with no message content, and notes that conversation counts are filtered by org AI access settings — a non-obvious behavioral caveat that affects interpretation of the numbers.

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?

Two tight sentences, front-loaded with the summary label and then the enumerated contents. The long comma list is dense but each element maps to a distinct metric; the trailing caveat sentences are short and each earns its place.

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 is a zero-arg read with an output schema, so return-value detail is not required. The description fully enumerates what fields to expect and flags the AI-access filtering caveat, leaving only minor gaps around latency or freshness of the counts.

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?

There are zero parameters, so the baseline is 4. The description correctly does not waste words on inputs and instead spends its budget describing the aggregate contents, which is the right trade-off for a no-arg tool.

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?

Names a specific resource (business snapshot) and enumerates exactly what is aggregated: conversation/message counts, contacts, active campaigns, open and overdue tasks, new signals, due alarms, pending scheduled messages, and per-channel WhatsApp connection status. Clearly distinguishes itself from siblings like get_period_report, get_usage_summary, and get_message_stats as a single-call dashboard rather than a parameterized report.

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 'aggregate business snapshot' framing implies usage (a quick at-a-glance dashboard) but never states when to use this versus get_period_report or get_message_stats, nor any prerequisites such as requiring an org context. Usage is inferable from the enumeration rather than explicit.

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