generate_telemetry_funnel_blueprint

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

No annotations are provided, so the description carries the full burden. It clearly states that it 'generates' schemas, which implies a non-destructive, likely read-only operation. However, it does not specify any side effects (e.g., whether it writes files, calls external APIs, or has rate limits) or confirm that it is safe to call repeatedly. For a generation tool this is generally acceptable, but the lack of explicit non-mutating language leaves some ambiguity.

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 a single, densely packed sentence that front-loads the core action and resource. It avoids fluff and effectively conveys the essential information. It could be slightly more structured (e.g., separating use cases), but it is appropriately concise and highly readable.

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?

There is no output schema, so the description should clarify what the tool returns (e.g., format of the generated schemas). It does not state whether the output is JSON, code snippets, or a written document, nor does it mention any limitations or edge cases. Given the tool's low complexity (2 params) and clear purpose, this is a noticeable gap but not critical for selection. An agent could call it and discover the format, but it is incomplete.

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?

The schema covers 100% of parameters with descriptions for both app_name and analytics_provider. The description adds context about the purpose of the generated schemas but does not enhance understanding of what the parameters control beyond the schema's own descriptions. Per the rubric, with full schema coverage the baseline is 3, and the description does not elevate beyond that.

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 clear verb ('generates') and resource ('product event telemetry schemas') and explicitly lists the target providers (PostHog, Mixpanel, Plausible) and use cases (signup conversion, onboarding milestones, feature usage, churn signals). This distinguishes it from sibling tools like generate_observability_blueprint, which focus on broader observability rather than product event telemetry. The purpose is unambiguous.

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 provides strong context on when to use the tool by enumerating the specific tracking scenarios it handles. It does not explicitly compare to alternatives or state when not to use it, but the use-case clarity allows an agent to deduce when this tool applies relative to others. No exclusions are mentioned, so it falls short of an explicit when/when-not directive.

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