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by valentil

Request a commercial license

request_commercial_license

Start the commercial licensing process by submitting your name, email, and company. Your request is recorded locally, and you receive a URL and email to complete a signed agreement.

Instructions

Start the commercial licensing process. Records the request locally (for the licensor's CRM) and returns the licensing URL and email to complete a signed agreement. After the licensor issues a key, use activate_license.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesYour name / point of contact.
emailYesContact email.
notesNoAnything else the licensor should know.
seatsNoApproximate number of seats needed.
companyYesCompany / organization name.
Behavior4/5

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

The description adds behavioral context beyond annotations. Annotations indicate non-read-only, non-idempotent, non-destructive, and open-world. The description confirms it writes to a local CRM and interacts externally by returning a URL/email. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two sentences) and front-loaded with the core purpose. Every sentence adds meaningful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the parameter count, lack of output schema, and annotations, the description adequately explains the workflow: records locally, returns URL/email, then activate_license. It could be more specific about the output format, but it is sufficient for an agent to understand the flow.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for all parameters. The tool description does not add extra meaning beyond the schema's parameter descriptions, so it meets the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: starting the commercial licensing process. It specifies that it records the request locally for CRM and returns a URL and email to complete a signed agreement. It also distinguishes from the sibling 'activate_license' by noting to use that after a key is issued.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool: to start a commercial license. It provides guidance on the next step ('After the licensor issues a key, use activate_license'), which implies when not to use it (before key issuance). However, it does not explicitly compare with other related tools or state when not to use it.

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

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