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

With no annotations supplied, the description carries the entire burden of behavioral disclosure and delivers none of it: no indication of whether the tool reads or mutates anything, what authorization or data it needs, whether calls are expensive or rate-limited. Worse, calling the deliverable a 'copy-paste prompt pack with examples' actively misdescribes the interaction model, leaving the agent unsure whether it is invoking an analysis or retrieving static content.

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?

It is short, but almost every phrase is filler or sales copy — 'production-ready', 'repeatable workflow you can run today', 'delivered as a copy-paste prompt pack with examples' — rather than substance front-loaded for an agent. The two sentences consume the whole budget without conveying what the tool does.

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?

No output schema and no annotations mean the description should explain what a 'diag' run returns and how to invoke it meaningfully, and it does neither; the 'prompt pack' framing likely increases confusion about invocation. For a tool that is nominally an analysis routine, the definition is too thin for an agent to call it confidently.

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 is a single optional parameter whose schema description is already complete ('Optional user query to scope the analysis'), so the schema does the work. The description adds no meaning about how a query scopes the diagnosis or what happens when it is omitted — the baseline 3 for full schema coverage applies.

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 restates the tool name ('funnel diag tool system') and wraps it in marketing framing ('production-ready', 'repeatable workflow', 'copy-paste prompt pack') without ever stating the specific verb and resource — e.g. whether it diagnoses conversion drop-off, scores funnel stages, or produces a report. It also gives no basis for distinguishing it from the adjacent funnel-analyze-tool, funnel-formula-tool, or funnel-tpl-tool siblings.

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 only contextual hint is the audience ('marketing and operations leaders'); there is no when-to-use, no when-not-to-use, and no reference to any of the four sibling funnel tools. An agent choosing between funnel-diag-tool and funnel-analyze-tool has nothing to route on. 'Run today' is promotional, not guidance.

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