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Create a Keywordise account

create_account

Register a new Keywordise account from the terminal and receive an API key for it. Requires accept_terms=true: the person accepts the Terms and Privacy Policy (https://keywordise.com/terms) and authorises Keywordise to apply for jobs on their behalf. A confirmation email is sent; applying opens once the address is confirmed. Trial: 7 days and 27 applications, then Starter at $24.99/month (500 applications) or Pro at $49/month (1,000).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYes
passwordYes
accept_termsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (which only mark this as a non-idempotent write), the description discloses substantial behavior: a confirmation email is sent, applying is gated on address confirmation, and the trial/paid plan terms. This is exactly the kind of side-effect and prerequisite context annotations cannot convey.

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

Conciseness4/5

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

Front-loaded with the action and requirement, then flows into consequences. The trial and pricing details are on the verbose side but are decision-relevant context rather than padding.

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?

For a mutation tool with no output schema, the description covers prerequisites, side effects, and the gating flow, and it names the API key returned. It is complete enough to invoke correctly, though it doesn't detail error/validation behavior.

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 0%, so the description must carry the load. It explains accept_terms meaningfully (accepting Terms/Privacy and authorising job applications on the user's behalf), but email and password are left to the schema's format/length constraints with no added meaning.

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 opens with a specific verb and resource ('Register a new Keywordise account') and states the outcome ('receive an API key for it'). It is clearly distinguishable from siblings like login, create_api_key, and get_account.

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?

It states the key precondition (accept_terms=true) and the post-registration flow (confirmation email, applying opens after confirmation), giving clear context for when this applies. It does not explicitly contrast against login for existing accounts, so it stops short of full when/when-not routing.

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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