Signal Attribution

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

With no annotations, the description carries the full burden and it does disclose a meaningful behavioral trait: the tool depends on upstream tagging and returns nothing when that tagging is missing, which the agent should interpret as a data-quality finding rather than a bug. It does not state read-only vs mutation or any permission requirements, so a small gap remains.

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 purpose is front-loaded in the first sentence, followed by a short rationale and a caveat. Each sentence carries weight, though the editorial aside about it being 'the single most useful line' is slightly 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?

The output schema covers the return format, so no explanation of results is needed, and the description handles purpose, precondition, and empty-result interpretation. However, it is silent on the date-range parameters that scope the analysis, leaving the agent without guidance on how to constrain the query.

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%, and the description never mentions the two parameters (date_from, date_to) at all — no format, no expected range, no default behavior. The agent must infer from the schema alone that these are date bounds, which is a clear compensation gap.

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 verb and resource: reports which signal type and campaign produced booked meetings. An agent can tell this apart from stats-oriented siblings like get_campaign_stats or get_workspace_stats by the attribution framing. It stops short of explicitly naming a sibling it supersedes or complements.

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?

Gives a clear use context (the monthly report line) and an explicit precondition: it only works if leads were tagged with signal type at import. It also pre-empts a likely confusion by stating that an empty result is itself the finding. No explicit alternative tool is named, but the when-to-use guidance is concrete.

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