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Analyzing token quant scores

token_quant_scores
Read-only

Get Nansen Score Indicators for a token - quantitative risk and reward signals.

Use this tool when assessing a token's risk/reward profile, evaluating buy/sell decisions, or when the user needs quantitative data to make trading decisions.

Returns: Token risk/reward indicators as markdown with interpretation guidance.

Token info:
- **Market Cap**: Current market cap in USD
- **Market Cap Group**: largecap (>$1B), midcap ($100M-$1B), or lowcap (<$100M)
- **Is Stablecoin**: Whether token is a stablecoin (some indicators don't apply to stablecoins)

Fields returned per indicator:
- **Score**: Signal classification (bullish/neutral/bearish for reward; low/medium/high for risk)
- **Signal**: Raw numeric value of the indicator
- **Percentile**: Rank vs same market cap group (0-100%)
- **Last Trigger**: Date when signal was last calculated

Indicator types:
- **Reward Indicators**: price-momentum, funding-rate, chain-fees, chain-tvl, protocol-fees, trading-range
- **Risk Indicators**: btc-reflexivity, liquidity-risk, token-supply-inflation, concentration-risk, cex-flows

Notes: - Not all indicators available for every token/chain combination - Percentile compares against same market cap group (largecap >$1B, midcap $100M-$1B, lowcap <$100M)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / $defs
      Removed value: -{
-  "TokenQuantScoresRequest": {
-    "description": "Request model for Nansen Score Indicators endpoint (flattened).",
-    "properties": {
-      "chain": {
-        "default": "ethereum",
-        "description": "Blockchain chain (ethereum, solana, base, bnb, polygon, arbitrum, etc.). On-chain tokens only — Hyperliquid perps NOT supported.",
-        "type": "string"
-      },
-      "tokenAddress": {
-        "description": "Token contract address",
-        "type": "string"
-      }
-    },
-    "required": [
-      "tokenAddress"
-    ],
-    "type": "object"
-  }
-}
    • addedInput schema / additionalProperties
      Added value: +false
    • changedInput schema / properties / request / anyOf
      Previous value: -[
-  {
-    "additionalProperties": true,
-    "type": "object"
-  },
-  {
-    "$ref": "#/$defs/TokenQuantScoresRequest"
-  }
-]New value: +[
+  {
+    "additionalProperties": true,
+    "type": "object"
+  },
+  {
+    "description": "Request model for Nansen Score Indicators endpoint (flattened).",
+    "properties": {
+      "chain": {
+        "default": "ethereum",
+        "description": "Blockchain chain (ethereum, solana, base, bnb, polygon, arbitrum, etc.). On-chain tokens only — Hyperliquid perps NOT supported.",
+        "type": "string"
+      },
+      "tokenAddress": {
+        "description": "Token contract address",
+        "type": "string"
+      }
+    },
+    "required": [
+      "tokenAddress"
+    ],
+    "type": "object"
+  }
+]
  2. Changed1 schema field changed
    • changedInput schema / $defs / TokenQuantScoresRequest / properties / chain / description
      Previous value: -"Blockchain chain (ethereum, solana, base, bnb, polygon, arbitrum, etc.)"New value: +"Blockchain chain (ethereum, solana, base, bnb, polygon, arbitrum, etc.). On-chain tokens only — Hyperliquid perps NOT supported."
  3. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it explains the output structure (Score, Signal, Percentile, Last Trigger), notes that not all indicators are available for every token/chain combination, and mentions that some indicators don't apply to stablecoins. This goes beyond the annotations and gives the agent a clear picture of what to expect. No contradictions with 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?

The description is well-structured and front-loaded with purpose and usage, then details the output format and indicator types. It is somewhat long but every section adds value — the output field explanations and indicator categories are necessary for correct interpretation. No fluff, so it earns a 4.

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 tool's complexity (multiple indicator types, percentile comparisons, caveats), the description is fairly complete. It explains the output fields, indicator categories, and the note about availability. It does not explicitly state that a token address is required, but the schema makes that clear. The output schema exists, so return values are covered. Minor gaps exist (e.g., error handling, prerequisites), but overall the description provides enough context for an agent to use the tool correctly.

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

Parameters2/5

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

Schema description coverage is 0% — the tool description does not explain how to construct the 'request' parameter. The schema itself includes descriptions for 'chain' and 'tokenAddress', but the 'request' wrapper is an anyOf with two object types, which could confuse an agent. The description does not compensate by explaining that the tool requires a token address and chain, nor does it clarify the anyOf structure. With low schema coverage, the description was expected to fill the gap but does not, so this dimension scores low.

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 opens with a clear statement of what the tool does: 'Get Nansen Score Indicators for a token - quantitative risk and reward signals.' It specifies the resource (token) and action (get), and distinguishes itself from siblings like token_technical_indicators by focusing on risk/reward scoring. The purpose is unambiguous and specific.

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?

The description explicitly states when to use the tool: 'Use this tool when assessing a token's risk/reward profile, evaluating buy/sell decisions, or when the user needs quantitative data to make trading decisions.' This provides clear context. It does not mention when not to use it or alternative tools, but the explicit positive guidance is strong, so it earns a 4 rather than a 5.

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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