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by io.github.pipeworx-io
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Get Collection Stats

get_collection_stats
Read-onlyIdempotent

Floor price, volume (24h/7d/30d/all), supply, owners, and best-offer for a collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_slugYesOpenSea collection slug

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCollection slug
intervalsYesTime-windowed statistics (24h, 7d, 30d)
market_capYesCollection market cap
num_ownersYesNumber of unique owners
floor_priceYesFloor price in ETH or native token
total_salesYesTotal number of sales all-time
total_volumeYesTotal trading volume all-time
average_priceYesAverage sale price all-time

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "collection_slug": "cryptopunks"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "average_price": {
+      "description": "Average sale price all-time",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "floor_price": {
+      "description": "Floor price in ETH or native token",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "intervals": {
+      "description": "Time-windowed statistics (24h, 7d, 30d)",
+      "items": {
+        "properties": {
+          "average_price": {
+            "description": "Average price in interval",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "sales": {
+            "description": "Number of sales in interval",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "volume": {
+            "description": "Volume in interval",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "volume_change_pct": {
+            "description": "Volume change percentage",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "window": {
+            "description": "Time interval (24h, 7d, 30d)",
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "market_cap": {
+      "description": "Collection market cap",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "num_owners": {
+      "description": "Number of unique owners",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "slug": {
+      "description": "Collection slug",
+      "type": "string"
+    },
+    "total_sales": {
+      "description": "Total number of sales all-time",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "total_volume": {
+      "description": "Total trading volume all-time",
+      "type": [
+        "number",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "slug",
+    "floor_price",
+    "market_cap",
+    "total_volume",
+    "total_sales",
+    "average_price",
+    "num_owners",
+    "intervals"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations (readOnlyHint, idempotentHint, destructiveHint) already declare safe read-only behavior. Description adds no further behavioral details beyond listing output fields, which is adequate but not enriching.

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?

Very concise single sentence listing key fields. Efficient but lacks structural front-loading of the main purpose; however, it's not wasteful.

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?

Given one required param, existing output schema, and low complexity, the description fully covers what the tool returns, making it complete for its purpose.

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 covers 100% of the single parameter with a clear description. The description does not add additional meaning or explain how to find a valid slug, so baseline score 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?

Description explicitly lists the specific metrics returned (floor price, volume, supply, owners, best-offer) for a collection, clearly distinguishing it from siblings like get_collection or get_nft which provide broader or different data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like get_collection or list_collection_nfts. Missing context about prerequisites or when not to use it.

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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