The Quartermaster

List graded makers

quartermaster_list_makers

Read-onlyIdempotent

List menswear makers graded in the QuarterMaster ledger, best first, optionally filtered by category, minimum grade, and how their off-price stock behaves. Use for menswear questions like "who makes good boots", "best jeans that last" or "which shirt brands are worth it". Limits: menswear only; prices are US dollars from the QuarterMaster ledger of 53 makers, checked September 2026, not live store prices; no stock, size or delivery checks; no orders.

Input Schema

Name	Required	Description
`category`	No	One of: shoes (Leather shoes), boots (Boots), sneakers (Sneakers), tailoring (Suits, jackets, trousers), shirts (Shirts), knitwear (Knitwear), outerwear (Outerwear), watches (Watches), denim (Jeans), tees (Tees and polos), chore (Chore jackets and overshirts), chinos (Chinos and cotton trousers).
`min_grade`	No
`off_price`	No	mainline: off-price stock is the real line; made-for-outlet: a cheaper line under the same name; rare: seldom discounted.

Output Schema

Name	Required	Description	Default
`count`	Yes
`makers`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 28, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "count": {
+      "minimum": 0,
+      "type": "integer"
+    },
+    "makers": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "categories": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "dossier": {
+            "type": "string"
+          },
+          "full_price": {
+            "anyOf": [
+              {
+                "additionalProperties": false,
+                "properties": {
+                  "high": {
+                    "type": "number"
+                  },
+                  "low": {
+                    "type": "number"
+                  }
+                },
+                "required": [
+                  "low",
+                  "high"
+                ],
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "grade": {
+            "enum": [
+              "S",
+              "A",
+              "B",
+              "C",
+              "D"
+            ],
+            "type": "string"
+          },
+          "id": {
+            "type": "string"
+          },
+          "maker": {
+            "type": "string"
+          },
+          "off_price_stock": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "maker",
+          "id",
+          "grade",
+          "categories",
+          "full_price",
+          "off_price_stock",
+          "dossier"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "count",
+    "makers"
+  ],
+  "type": "object"
+}

First observedSep 27, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavior: results are ordered best-first, the data is a static snapshot (ledger of 53 makers, checked September 2026, not live store prices), and it explicitly does no stock/size/delivery checks. The data-freshness caveat is not derivable from the annotations.

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 purpose, then intent examples, then a Limits block, so each sentence has a job. It is dense but not padded; the three-part structure is easy to scan.

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?

An output schema exists, so return values need no explanation, and the description covers scope (menswear), data provenance and freshness, ordering, and the tasks it deliberately excludes. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%, and the description names the three filter axes (category, minimum grade, off-price stock behavior) but adds little syntax or detail beyond the schema. min_grade has no schema description, so the description's 'minimum grade' is a marginal contribution; baseline 3 is appropriate.

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 verb (List) and resource (menswear makers graded in the QuarterMaster ledger), plus ordering (best first) and optional filters. It is clearly distinguishable from siblings like quartermaster_get_maker or quartermaster_check_piece without opening any schema.

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?

Provides concrete example questions ('who makes good boots', 'best jeans that last') that anchor the tool to real queries, and the Limits section states when not to use it (no stock, size, delivery, orders). It does not explicitly name an alternative sibling to route to, which keeps it just below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All The Quartermaster tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?