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Analog-Labs

Firestarter MCP Server

by Analog-Labs

firestarter_seller_orders

Read-only

Check incoming seller orders for product, quantity, amount, net payout, order and payout status, and carrier tracking. Read-only; answers seller order and sales questions.

Instructions

View the seller's incoming orders — product, quantity, amount, net payout, order status, payout status, and carrier tracking when shipped. This is the start of the fulfillment flow: firestarter_seller_orders (see what sold) → firestarter_confirm_order (accept a pending order) → firestarter_ship_order (add tracking; the buyer is notified automatically). Use whenever a seller asks about their orders, sales, what sold, or recent activity. Covers all orders including those from a connected Shopify store. Each order line carries the order_id you pass to confirm/ship. Read-only: never changes anything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The annotations already state readOnlyHint=true and destructiveHint=false, so the bar is lower. The description reinforces 'Read-only: never changes anything' and adds valuable context: it covers all orders including connected Shopify stores, and the order_id carried on each line is directly passed to confirm/ship. This goes beyond the simple annotation flags.

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 well-structured with a clear lead sentence, a concise flow diagram, a usage trigger, and additional relevant details. It is somewhat longer than necessary, but every sentence provides useful information and the front-loading is effective.

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 no output schema, the description carries the burden of explaining what the agent will receive. It lists the data fields (product, quantity, amount, net payout, order status, payout status, tracking) and explains downstream use (order_id). For a read-only list tool, this is complete and actionable.

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?

There are zero parameters, so the description is not expected to explain parameter details. The baseline for 0 params is 4, and the description appropriately focuses on the output fields and workflow rather than parameters. No gaps exist.

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 resource: 'View the seller's incoming orders', and lists the key data fields. It explicitly differentiates itself from sibling tools by positioning itself as the start of the fulfillment flow (confirm_order, ship_order), making its purpose and scope unambiguous.

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?

Provides an explicit trigger: 'Use whenever a seller asks about their orders, sales, what sold, or recent activity.' It also maps the sequential flow with confirm_order and ship_order, implicitly telling the agent which tools to use next and effectively defining when this tool is appropriate versus the 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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