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JavaScript
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opensea_collection_trait_offers

List standing offers for a specific OpenSea collection trait, showing price levels with trait type and value to price rare items against the collection floor.

Instructions

List an OpenSea collection's trait offer book. Returns standing offers scoped to a specific trait value rather than the whole collection, as price levels with the trait type and value attached. Useful for pricing rare-trait items against the collection floor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesOpenSea collection slug
limitNoPrice levels per page, 1-100
cursorNoOpaque pagination cursor from a previous next_page_cursor
sort_directionNoSort direction by offer price

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort_direction / enum
      Added value: +[
+  "ASC",
+  "DESC"
+]
  2. Addedv1.16.2

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It adds useful context: returns 'standing offers' as 'price levels with the trait type and value attached' and clarifies the trait-scoped granularity. However, it does not mention read-only status, authentication needs, rate limits, or pagination behavior beyond what the schema already implies, leaving gaps for a mutating-vs-read distinction that annotations would normally cover.

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?

Three sentences, front-loaded with the primary action, followed by scope detail and a concrete use case. Every sentence earns its place with zero redundancy or filler.

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?

For a 4-parameter tool with no output schema, the description adequately explains what the tool returns and why an agent would choose it. It could add more about pagination usage or explicitly contrast with collection-wide offer tools, but the schema already documents the pagination parameters, and the core selection/invocation context is present.

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 all four parameters are already documented. The description adds contextual meaning about 'price levels' and trait scoping that helps an agent understand what slug/limit mean semantically, but it provides no additional syntax, format, or parameter-specific detail beyond the schema. 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?

The description names a specific verb and resource ('List an OpenSea collection's trait offer book') and immediately clarifies scope: 'scoped to a specific trait value rather than the whole collection.' This distinguishes it from collection-wide offer siblings like opensea_collection_offers and from trait-listing tools like opensea_collection_traits, without needing to open the 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?

The description gives a clear use case ('Useful for pricing rare-trait items against the collection floor') and contrasts with the whole-collection alternative, so an agent can infer when this tool is appropriate. It stops short of explicitly naming sibling tools or stating when-not-to-use, so it loses the top score.

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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