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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior. The description adds the modeling scope—monthly/annual new ARR and lagging pipeline ARR—but does not disclose assumptions, formula behavior, limitations, or return format.

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 core sentence is front-loaded and concise, covering the main modeling purpose. However, the second sentence is an external promotional link that does not help tool selection or invocation, so it does not fully earn its place.

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 convey return values. It names the modeled outputs conceptually but does not specify their format, units, or assumptions, leaving output behavior somewhat underspecified.

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%, and all four required parameters have clear descriptions in the schema. The description adds no units, constraints, or format details beyond what the schema already provides, so the baseline of 3 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?

States the specific verb 'Model' and the resource/output well: monthly and annual new ARR from a freemium funnel, plus ARR lagging in the upgrade pipeline. This distinguishes it from generic ARR/MRR calculators, though it does not explicitly name a sibling alternative.

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?

There is no explicit when-to-use or when-not-to-use guidance. The freemium funnel framing implies the context, but it does not tell the agent how to choose this over related calculators such as mrr_to_arr_calculator or product_led_growth_feasibility_grader.

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