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GigSoul x402

generate-cold-email

Write a first-touch cold email for a product and audience: subject line, preview text, and a 100-150 word body. Use for the opening message. For the follow-ups after no reply, use generate-follow-up-sequence. To check spam risk before sending, use check-email-deliverability. Pay-per-call: $0.05 USDC on Base via x402. Without a payment-signature header the call returns an error whose data carries the payment terms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoThe product and the recipient type. Example: Invoice tool for freelance designers, to agency ops leads
contextNoOptional: prospect research, proof points, or tone.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Optional supporting text or content to analyze"New value: +"Optional: prospect research, proof points, or tone."
    • changedInput schema / properties / query / description
      Previous value: -"The question or input for this tool. Example: pitching x402 pay-per-call APIs to agent developers"New value: +"The product and the recipient type. Example: Invoice tool for freelance designers, to agency ops leads"
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and discloses the pay-per-call cost, payment method, and the error behavior when the payment-signature header is missing. This is important behavioral context beyond the schema.

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 four sentences, front-loads the main purpose, and packs usage guidance, alternatives, and payment details without unnecessary fluff. It is appropriately sized for the tool's complexity.

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

Completeness5/5

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

For a low-complexity tool with no output schema, the description covers output components, use case, alternatives, and payment/error behavior. An agent has enough context to select and invoke the tool correctly.

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% and both parameters already have descriptions, so the baseline is 3. The description adds little beyond restating that the email is 'for a product and audience,' which mirrors the query parameter.

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 output: 'Write a first-touch cold email' with subject, preview, and 100-150 word body. It distinguishes this from sibling tools by explicitly naming generate-follow-up-sequence and check-email-deliverability.

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?

It explicitly says 'Use for the opening message' and directs to generate-follow-up-sequence after no reply, and check-email-deliverability to check spam risk. This gives an agent clear when-to-use and when-not-to-use guidance with named alternatives.

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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