Ship Check

Request a project estimate

request_estimate

Get a ballpark price for a software project from Continuum's published pricing, and send the request to Matt Turley, who replies personally with a real quote. Use it when the user asks what a build, fix, review, ongoing support or AI-search visibility work would cost. The ballpark is the matching published offer(s) and price range from uxcontinuum.com/pricing, not a quote. Show it to the user labeled that way. Then offer a call: get_availability and book_call.

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": {
      "project_description": "<project_description>",
      "name": "<name>",
      "email": "<email>"
    },
    "name": "request_estimate"
  }
}

Input Schema

Name	Required	Description
`name`	Yes	The user's name.
`email`	Yes	The user's own email, for Matt's quote.
`budget`	No
`timeline`	No
`project_type`	No	launch-review (check an app before launch), fix-existing-app (stabilize or rescue an app), new-build (MVP from scratch), ongoing-support (maintenance or a product team on retainer), ai-visibility (get recommended by ChatGPT and AI search), other. Inferred from the description if omitted.
`project_description`	Yes	What the user wants built or fixed, 10 to 4000 characters.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Adds substantial context beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false): the request is delivered to a specific person who replies personally, the returned ballpark is explicitly NOT a quote and must be shown to the user labeled as such, and the workflow continues by offering a call. That is real behavioral disclosure of a non-idempotent, human-routed write.

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?

Purpose and the pricing source are front-loaded, and the multi-step flow (show ballpark → offer call) is ordered logically. It is dense but each sentence carries information; only the repeated framing of 'ballpark vs. quote' is slightly redundant.

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?

No output schema exists, and the description usefully explains the return semantics (matching published offer(s) plus price range, labeled as a ballpark) and the post-call handoff. The two undocumented optional parameters (budget, timeline) and the absence of any confirmation/permission step before sending user contact details are the remaining gaps.

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 description coverage is 67%: name, email, project_type and project_description are documented, while budget and timeline are not. The description echoes the project_type categories in prose ('build, fix, review, ongoing support or AI-search visibility'), adding slight value, but contributes nothing about budget/timeline. Baseline 3 for mid coverage.

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 precise verb+resource: it fetches a ballpark price from Continuum's published pricing AND sends a request to a named human (Matt Turley). This is clearly separable from the sibling cost-estimator tools (agent_cost_estimate, cursor_auto_cost_estimate, swarm_run_cost_estimate), which estimate compute/agent costs rather than project pricing.

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?

Gives an explicit trigger — 'Use it when the user asks what a build, fix, review, ongoing support or AI-search visibility work would cost' — and names the follow-on tools (get_availability, book_call). It does not state a when-not condition or contrast against the similarly-named cost-estimate siblings, so it stops short of a full 5.

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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