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

Annotations only say non-read-only, open-world, non-destructive; the description adds the important behavior that a request is actually dispatched to a human maker by email, who replies within one business day, and that agent-submitted requests are treated as sent with user permission. That is meaningful side-effect and consent context beyond the annotations. It does not cover edge cases such as what happens if contact_email is omitted or whether duplicate requests are deduplicated.

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 front-loaded with the value proposition (fixed price and scope) and the return payload (price, timeline, inclusions, next steps) before the procedural details. Slightly long with three near-paraphrased examples and the parenthetical '(or you)', but almost every sentence carries information an agent needs.

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?

For a six-parameter, no-output-schema tool, the description covers what comes back (price, timeline, inclusions, how to proceed), the asynchronous human-in-the-loop flow, and the consent framing. The main gap is behavior when optional contact fields are omitted, and there is no mention of how the quote is delivered back to the caller.

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?

With 67% schema coverage, the schema already explains task, how_often, workflows and tools_involved, and the description adds real meaning for the two undocumented params: contact_email sends the request to the maker and contact_name accompanies it. The examples also flesh out what 'task' should look like in practice. It adds little for workflows or tools_involved beyond what the schema already says.

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 names a specific outcome (a fixed price and scope for a custom automation build and deployment by Gragg Robotics) and concretely scopes what counts as an automation with three examples. It is clearly distinguishable from siblings like list_free_calculators (free calculators) and request_product (product requests) because it is explicitly a quote for a bespoke human-delivered build.

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 a clear qualifying condition ('a task that should keep running without them or you doing it by hand') plus examples, and explains the follow-up path via contact_email with a one-business-day reply promise. It stops short of naming when NOT to use it or pointing at a sibling (e.g. free calculators or product requests) for simpler needs, so routing between siblings is only implied.

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