chatwoot_get_inbox_label_matrix

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent with a read-only reporting tool. The description adds no further behavioral context such as rate limits, auth requirements, or edge-case behavior, so it does not go beyond the annotation-provided safety profile.

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 front-loads the result and use case, then lists all four parameters compactly. Minor redundancy exists in 'period: Analysis period' and 'output_format: Output format', but overall the structure is efficient and scannable.

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 that an output schema exists and annotations cover the safety profile, the description is largely complete: it explains the tool's output, its analytical use case, and how to source inbox/label IDs. The only notable gap is not naming sibling tools for comparison, but this is not critical for invocation.

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 0%, so the Args section is essential. It adds real meaning for inbox_ids and label_ids by defining them as filters and pointing to chatwoot_list_inboxes and chatwoot_list_labels. period and output_format are minimally restated, but their allowed values are already provided by schema enums and defaults.

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 first sentence states a specific result: 'Returns the conversation distribution between inboxes and labels' and clarifies the shape as an 'inbox × label matrix'. This is distinct from the single-dimension sibling analytics tools like label or inbox performance, so an agent can identify what this tool uniquely provides.

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 gives a clear use case: 'understanding which channels generate which types of conversations.' It doesn't explicitly contrast with sibling analytics tools or state when not to use it, but it provides enough context for an agent to select it for cross-cutting inbox/label analysis.

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