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Faire MCP Server and API by Cotlet

by dev.cotlet
OverviewDiscussionsAdmin

Create reorder in Faire

faire_create_reorder
Read-onlyIdempotent

Create reorder in the user's own Faire account from ChatGPT, Claude or any AI agent. Returns how to do it in Faire step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Faire Cloud Browser. Faire's official API: Yes, but only part of it: Faire has an External API for brands that covers products, orders and inventory, and a single brand can generate its own access token in the brand portal (checked 11 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "faire_create_reorder"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the annotations (readOnly, idempotent, non-destructive, closed-world), the description adds the key behavioral fact that the tool performs no action itself and only returns a guide, plus that execution happens in a cloud browser session. The trailing paragraph about Faire's External API is background context rather than behavior of this tool, so it adds less value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core sentences are front-loaded and useful, but the final sentence about Faire's External API coverage is tangential to invoking this tool and reads as filler. The remaining content is efficient, but that paragraph dilutes focus.

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?

With no parameters, no output schema, and simple annotations, the definition covers what an agent needs: what the tool returns and that the agent must drive the browser separately. It does not describe the shape of the returned steps (plain text vs. structured) or whether authentication to the Faire account is required.

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?

The tool takes zero parameters, so there are no semantics for the description to add and the baseline is 4. The description correctly implies no input is needed by describing the call as a request for a procedure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description concretely states the tool returns step-by-step instructions (screens, buttons, fields) for creating a reorder in the user's Faire account, and explicitly clarifies it 'opens nothing by itself'. This resolves the tension between the 'create' name and readOnlyHint=true. It does not explicitly differentiate itself from the related cotlet_app_guide sibling, which keeps it from a 5.

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?

It clearly lays out the workflow: call this to get the procedure, then execute it with the cotlet_browser_* tools in the user's Faire Cloud Browser. That sequencing is genuinely actionable. It lacks explicit 'when-not' conditions, such as when to prefer an API-based sibling or cotlet_app_guide instead.

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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