Ship Check

Request a human review ($299)

request_human_review

Get a senior engineer (Matt Turley, 20 years shipping software) to review by hand the app behind a ship_check scan: the paid $299 Ship Check. Returns a Stripe Checkout link and a call booking link for the user to open themselves. This call charges nothing and never pays on the user's behalf. Only call it when the user asks for a human review or agrees to one. Pass the user's own email so Matt can follow up personally; no automated email is sent to it. Show the user checkout_url and booking_url.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "scan_id": "<scan_id>",
      "email": "<email>"
    },
    "name": "request_human_review"
  }
}

Input Schema

Name	Required	Description	Default
`email`	Yes	The user's email, for the checkout and for Matt to reply to.
`scan_id`	Yes	The scan_id returned by ship_check.

Output Schema

Name	Required	Description
`url`	Yes
`price`	Yes
`scan_id`	Yes
`report_url`	Yes
`booking_url`	Yes	Book a 30-minute call with Matt instead of, or before, paying.
`checkout_url`	Yes	Stripe Checkout for the human review. The user opens and pays it themselves.
`what_happens_next`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the annotations (readOnly=false, idempotent=false, openWorld=true), it discloses the concrete side effects and limits: it returns a Stripe Checkout link and booking link for the user to open, charges nothing itself, never pays on the user's behalf, and sends no automated email. That is exactly the context an agent needs before invoking a paid flow.

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?

The description is a bit long at five sentences, but each one carries distinct payload (who, what, what it returns, when to call, what to do with the result) and the key facts are front-loaded.

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?

With an output schema present, the description needn't enumerate return fields, yet it still tells the agent to surface checkout_url and booking_url to the user, closing the loop on the payment-flow handoff.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: the email must be the user's own so Matt can follow up, and no automated email is sent to it — clarifying both intent and a non-obvious non-behavior.

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 (hand-review of the app behind a ship_check scan) and names the exact artifact it operates on, plus the price. It is clearly distinguishable from ship_check (which produces the scan) and book_call (which books directly).

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 gating condition: 'Only call it when the user asks for a human review or agrees to one.' That is a clear when-to-use rule and an implicit when-not for every other case, leaving nothing to inference.

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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