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Custom Blinds Shop

by io.github.CustomBlinds
OverviewDiscussionsAdmin

request_swatch

Log up to 5 colour codes against an EXISTING order for the team (order_ref required; without it the tool returns status order_required and logs nothing). Custom Blinds does not post individual swatches or off-cuts. For orders over R8,000 the customer can ask for the full sample book via WhatsApp; if nothing suits, full refund with no fees. Never quote a sample-book price or courier cost.

Input Schema

NameRequiredDescriptionDefault
suburbNoOptional delivery suburb
order_refYesThe order reference the swatches ship with. Required.
swatch_codesNoOptional specific colour codes (max 5)
customer_nameYesCustomer's full name.
customer_emailYesCustomer's email address.
customer_phoneYesUsed as WhatsApp number
product_interestYese.g. 'Roller Blockout' or 'Honeycomb'

Output Schema

NameRequiredDescriptionDefault
policyNo
statusYes
messageYes
next_stepNo
order_refNo
request_idNo
swatch_countNo
estimated_delivery_daysNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / customer_email / description
      Added value: +"Customer's email address."
    • addedInput schema / properties / customer_name / description
      Added value: +"Customer's full name."
  2. Changed7 schema fields changed
    • addedInput schema / properties / order_ref
      Added value: +{
+  "description": "The order reference the swatches ship with. Required.",
+  "type": "string"
+}
    • changedInput schema / properties / swatch_codes / description
      Previous value: -"Optional specific colour codes; no count limit enforced by this handler"New value: +"Optional specific colour codes (max 5)"
    • changedInput schema / required
      Previous value: -[
-  "customer_name",
-  "customer_email",
-  "customer_phone",
-  "product_interest"
-]New value: +[
+  "customer_name",
+  "customer_email",
+  "customer_phone",
+  "product_interest",
+  "order_ref"
+]
    • addedOutput schema / properties / next_step
      Added value: +{
+  "type": "string"
+}
    • addedOutput schema / properties / order_ref
      Added value: +{
+  "type": "string"
+}
    • addedOutput schema / properties / policy
      Added value: +{
+  "type": "string"
+}
    • changedOutput schema / required
      Previous value: -[
-  "request_id",
-  "status",
-  "estimated_delivery_days",
-  "swatch_count",
-  "message"
-]New value: +[
+  "status",
+  "message"
+]
  3. Changed2 schema fields changed
    • changedInput schema / properties / swatch_codes / description
      Previous value: -"Optional specific colour codes (max 5)"New value: +"Optional specific colour codes; no count limit enforced by this handler"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "estimated_delivery_days": {
+      "additionalProperties": true,
+      "properties": {
+        "max": {
+          "type": "number"
+        },
+        "min": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "min",
+        "max"
+      ],
+      "type": "object"
+    },
+    "message": {
+      "type": "string"
+    },
+    "request_id": {
+      "type": "number"
+    },
+    "status": {
+      "type": "string"
+    },
+    "swatch_count": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "request_id",
+    "status",
+    "estimated_delivery_days",
+    "swatch_count",
+    "message"
+  ],
+  "type": "object"
+}
  4. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Adds meaningful behavior beyond the annotations: without order_ref it returns status order_required and logs nothing. It also discloses business constraints around sample books, refunds, and not quoting prices or courier costs.

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?

Front-loads the core action and the order_ref requirement. Later sentences carry important guardrails, though the sample-book/refund policy sentence is slightly long.

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?

Given the output schema and annotations, the description supplies the key operational context: existing-order requirement, failure behavior, and what not to promise. It is largely complete for correct invocation.

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%, so the baseline is 3. The description adds semantic value by emphasizing order_ref as required and explaining the concrete failure outcome when it is missing.

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 specific action ('Log up to 5 colour codes') tied to a specific resource ('against an EXISTING order'), and the scope makes it distinguishable from swatch-stock and WhatsApp-handoff siblings.

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?

Clearly says this is for existing orders, requires order_ref, and rules out individual swatches/off-cuts. It also gives an alternative path for orders over R8,000 via WhatsApp, though it does not directly name sibling tools.

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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