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

Beyond the read-only annotations, the description discloses important behavioral context: first-touch attribution, assisted-conversion counting, the exact definition of a customer (won stage, placed order, or offline sale), ready-made highlights, and the fact that ad spend is not included. These details materially affect how the agent should interpret the output.

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 dense and front-loads the core metrics and scope, with no filler sentences. It is longer than average because it defines attribution and customer semantics, but nearly every clause carries useful meaning for this complex reporting tool.

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 appropriately explains that the answer should come from `summary` and describes the kinds of highlights present. It does not document the full return shape, but it gives enough context for an agent to invoke and interpret the report correctly.

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 the parameters `days`, `site_id`, and `user_goal` are already documented in the schema. The description reinforces the look-back window with "last N days" but adds no syntax, defaults, or additional meaning 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 states a specific reporting purpose: leads, customers, conversion rate and revenue by source and campaign over the last N days. It explicitly names attribution (first touch), assisted conversions, and predefined highlights, which makes it clearly distinct from sibling tools like get_post_performance or list_marketing_campaigns.

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?

It gives concrete use-case phrases such as "which campaigns are working" and "where do my customers come from," and tells the agent to answer from `summary`. It also explicitly excludes ad spend, but does not name an alternative tool for spend or for broader growth reporting.

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