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iwant.fyi - shop, price-check and keep looking

by fyi.iwant
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List supported verticals

demand.list_verticals
Read-only

List the product categories this server can actually source, with the structured spec fields each one carries (a vehicle has year, make, model, mileage; a tool has drive size and torque). Call it before a first search to learn which vertical values are accepted, or when a search returns nothing and you need to check the category is covered at all. Free, instant, no side effects. Protocol v1.0 §8.2.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
verticalsYesEvery vertical this server can match demand in.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "verticals": {
+      "description": "Every vertical this server can match demand in.",
+      "items": {
+        "properties": {
+          "description": {
+            "description": "What this vertical covers.",
+            "type": "string"
+          },
+          "key": {
+            "description": "Identifier to pass as the `vertical` argument, e.g. \"vehicles\".",
+            "type": "string"
+          },
+          "spec_keys": {
+            "description": "Structured spec fields carried for items in this vertical.",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          }
+        },
+        "required": [
+          "key"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "verticals"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'Free, instant, no side effects.' It adds context beyond the annotations by clarifying that this returns only categories the server can 'actually source' and references 'Protocol v1.0 §8.2', giving the agent confidence about scope without contradicting the structured hints.

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

Conciseness5/5

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

The description is three sentences with every sentence earning its place: purpose, usage timing, and side-effect safety. The core action and scope are front-loaded, and the protocol reference is kept to the end.

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 zero-parameter, read-only listing tool with an output schema, the description is complete. It covers what the tool returns, when to call it, and that it has no side effects, leaving no gap an agent would need to fill by opening the schema or guessing.

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 and schema coverage is 100%, so the baseline is 4. The description adds value by clarifying what the returned list contains (verticals plus their spec fields, e.g., vehicle vs tool), which helps an agent interpret the output schema correctly.

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 states a clear verb–resource pair: 'List the product categories this server can actually source' and further specifies that it includes 'the structured spec fields each one carries'. It differentiates itself from siblings like demand.search and demand.list_constraints by framing it as the pre-search way to learn accepted vertical values.

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?

The description gives explicit conditions for use: 'Call it before a first search to learn which vertical values are accepted, or when a search returns nothing and you need to check the category is covered at all.' It tells the agent both when and why to call it, which is strong practical guidance despite not naming a specific sibling alternative.

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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