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by io.github.CSteenkamp
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NFT trait prices

get_nft_trait_prices
Read-onlyIdempotent

Per trait value of an NFT collection: how many assets have it, how many are listed and the cheapest listing (floor, ADA), and the sales in the window with their average and highest price. Only assets whose traits have been read are included; the answer says how many of the collection that is (coverage). Use it to price a trait.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "policyId": "<policyId>"
    },
    "name": "get_nft_trait_prices"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoWindow for the sales in days: 7, 30, 90 or 365.
limitNoHow many trait values to return (1-100, default 25).
traitNoOnly this trait category (for example "Background").
policyIdYesNFT policy id: 56 hex characters. Get it from `search` or `list_nft_collections`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The annotations already establish this as a read-only, open-world, idempotent, non-destructive operation. The description adds meaningful behavioral context by disclosing that only assets whose traits have been read are included and that coverage is reported, which is important for interpreting results.

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 compact and front-loads the returned fields and key limitation. Every sentence contributes useful information, and the final usage sentence is placed well.

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?

With no output schema, the description does a good job explaining the main return values and the coverage caveat, while the input schema fully covers parameters. Minor gaps remain, such as result ordering and how trait values are selected when limit is applied.

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 description coverage is 100%, so the input schema already documents policyId, trait, days, and limit thoroughly. The description references the sales window and coverage but does not add parameter-level meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the resource and returned data: per-trait asset counts, listing counts, cheapest listing, and sales statistics for an NFT collection. It also says to use it to price a trait, which is specific. It does not explicitly distinguish this from sibling NFT tools such as get_nft_listings or get_nft_floor_history.

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 closing sentence, "Use it to price a trait," gives clear intended usage. It does not name alternatives or describe when not to use this tool versus other NFT market tools, so it falls short of full routing guidance.

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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