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opensea_collection_offers

List an OpenSea collection's offer book by price level, showing standing offers per price, total offer count, and aggregate value. Sort by price for market insight.

Instructions

List an OpenSea collection's offer book. Returns the collection-wide offer book as price levels: how many standing offers sit at each price per item, plus the aggregate offer count and total value across the whole collection. Offers are sorted by price.

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

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does well by explaining exactly what is returned: price levels, standing offer counts, aggregate offer count, total value, and that offers are sorted by price. This goes beyond a simple tautology and gives the agent a clear picture of the tool's behavior, though it omits details like pagination mechanics or potential rate limits.

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 efficient: two sentences with no redundancy. The first sentence states the core action, and the second elaborates on the output structure and ordering. Information is front-loaded and every clause adds value.

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 there is no output schema, the description adequately explains the return value: price levels, standing offer counts, aggregate count, and total value, plus sorting. It also makes clear the scope is collection-wide. It does not mention pagination details or default sort direction, but those are partially captured by the input schema (cursor, sort_direction). Overall, an agent has enough context to call this tool correctly.

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 schema already documents all parameters (slug, limit, cursor, sort_direction). The description adds no additional parameter semantics beyond what the schema provides, which aligns with the baseline of 3.

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 it 'List an OpenSea collection's offer book' and explains the output: price levels, standing offer counts, aggregate count and total value. It is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like opensea_collection_depth or opensea_item_offers, so it misses the top score for sibling distinction.

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?

There is no guidance on when to use this tool versus alternatives. The description simply states what it does without mentioning exclusions or when to prefer another OpenSea tool (e.g., opensea_collection_depth for order book depth or opensea_item_offers for item-level offers). An agent is left to infer usage context.

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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