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Northside Intelligence WebMCP

ni_services_reserve

Reserve a Northside Intelligence service project with a non-refundable deposit of 20% of that service's lowest price: intelligence audit $410, personal intelligence setup $50, workflow integration $1,010, custom web design $1,370, tailored intelligence server $5,140. The buyer's card is saved and the balance is charged when the service is complete; final price is confirmed after scoping. Returns a checkout_url and order_id; after payment call ni_order_status with order_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_nameYesCompany or individual client name
client_emailYesContact email
service_typeYesSelected service package
project_notesNoShort project notes, up to 200 characters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
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 of behavioral disclosure, and it excels: it states the non-refundable deposit, card being saved, balance charged upon completion, final price confirmed after scoping, and the return of checkout_url and order_id. This thoroughly informs the agent of side effects and required follow-up actions.

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 two sentences and every sentence contributes necessary information: pricing and deposit terms in the first, payment flow and follow-up in the second. It is slightly dense due to the price list, but it contains no filler, so it remains appropriately sized and front-loaded with the core purpose.

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 tool with no annotations and no output schema, the description is remarkably complete: it explains the deposit mechanics, pricing, what is returned (checkout_url and order_id), and the next step to check order status. An agent has enough to invoke the tool correctly and manage the follow-up workflow.

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% with descriptions for all parameters, so the baseline is 3. The description adds value by mapping service_type enum values to specific prices (e.g., 'intelligence audit $410'), which helps the agent select the correct service package. This goes beyond the schema's generic 'Selected service package' description.

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 clearly states the tool's action ('Reserve a Northside Intelligence service project') and its resource, and includes specific pricing for each service type, making it distinct from sibling tools like ni_order_status or ni_store_order. It also explicitly names the follow-up tool, further clarifying its role in the workflow.

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?

The description gives clear context for when to use this tool (to reserve a service with a deposit) and directs the agent to ni_order_status after payment, but it does not provide explicit exclusions or alternatives beyond that follow-up step. The workflow instruction is helpful, yet the 'when-not-to-use' guidance is implied rather than stated.

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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