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Ask for a ScrapeField account for the person you work for

sign_up

Ask for a ScrapeField API key for the person you work for. We email them a link; they sign in and type the code this returns, and only then is a key made. Show them user_code and tell them to check their email. Then call check_sign_up with id every few seconds until it is approved: the key comes once, in that answer. Keep id secret. An account an agent starts has no free credits: they buy a pack. Use this only when your person asked you to set ScrapeField up.

Input Schema

NameRequiredDescriptionDefault
agentNoWhat you are called, as the person knows you, e.g. "Claude Code". Shown to them in the email.
emailYesThe email address of the person you work for. The account is theirs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the email-verification handshake, that the key is returned only once inside check_sign_up's answer, that `id` must stay secret, and that agent-started accounts get no free credits. It does not specify what happens on failure/expiry or any polling rate limit, so it is strong but not exhaustive.

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?

Dense but front-loaded — the core ask comes first, then the flow, then the caveats. Every sentence carries information, though the sequence of constraints makes it slightly long for its size.

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?

There is no output schema, so the description must supply the return contract, and it does: it explains that `user_code` is shown to the user and that `id` drives the polling, with the key arriving in check_sign_up's response. Only failure modes and timing guidance are left implicit.

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%, so `agent` and `email` are already fully documented in the schema; the description adds no further input-side meaning. Notably, the values it names (`user_code`, `id`) are outputs of this call, not input parameters, so they don't enrich parameter semantics.

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?

States a specific action and resource: requesting a ScrapeField API key/account on behalf of the person the agent works for. It is clearly distinguishable from the data-fetching siblings and explicitly links to the check_sign_up sibling in the same flow.

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

Usage Guidelines5/5

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

Gives an explicit gate ("Use this only when your person asked you to set ScrapeField up") plus the downstream procedure: show `user_code`, have the person check email, then poll `check_sign_up` with `id` until approved. The when-to-use and next-step alternative are both spelled out.

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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