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Name Whisper — ENS Intelligence Layer

by ai.namewhisper

cancel_offer

DestructiveIdempotent

Cancel an active offer you made on an ENS name. Returns unsigned Seaport cancel() calldata.

Only the bidder (the order's offerer) can cancel. If the offer was cross-posted to OpenSea, you signed a second 'opensea' variant — pass BOTH order hashes as alsoCancel so one tx kills both.

Cancelling releases the WETH you'd committed to the offer — the buyer's wallet keeps its WETH balance free to bid elsewhere once the Seaport order is invalidated.

For cancelling your own listings, use cancel_listing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orderHashYesSeaport order hash of the offer to cancel (from get_name_details or the orderbook)
alsoCancelNoSibling order hashes to cancel in the same tx (e.g. the OpenSea-variant of an NW offer). Cancelling N orders costs barely more than cancelling one.
walletAddressYesWallet address of the bidder. Must match the original offerer on the order.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations indicate destructiveHint=true and idempotentHint=true. The description adds that it returns unsigned Seaport cancel() calldata, releases committed WETH, and invalidates the Seaport order. This enriches the behavioral context beyond annotations without contradiction.

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 5 purposeful sentences, front-loaded with the core action, then details on constraints, alternatives, and side effects. No filler or repetition.

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?

For a tool with 3 parameters, 100% schema coverage, and no output schema, the description fully explains the return type (unsigned calldata), the prerequisite (offerer identity), and the effect (WETH release). It answers likely agent questions.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds meaningful context: explains that walletAddress must match the original offerer, and that alsoCancel handles sibling orders like OpenSea variants, with a cost note. This goes beyond the schema's descriptions.

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 clearly states the tool cancels an active offer on an ENS name, with the verb 'cancel' and resource 'offer'. It distinguishes from the sibling 'cancel_listing' by explicitly mentioning 'For cancelling your own listings, use cancel_listing.'

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

Usage Guidelines5/5

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

It explicitly states who can cancel ('Only the bidder...') and when to use it (to cancel an offer). It provides specific guidance for cross-posted offers on OpenSea, requiring passing both order hashes. It also tells when not to use it by referencing the alternative 'cancel_listing'.

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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TDQS

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions, but some pairs (e.g., search_ens_names vs enumerate_entities, batch_purchase vs sweep) could cause confusion due to overlapping functionality. The descriptions help differentiate, but the large number of tools increases ambiguity risk.

Naming Consistency5/5

All tool names use consistent snake_case with a verb_noun pattern (e.g., get_name_details, set_ens_records, batch_create_listings). Naming conventions are uniform and predictable, making it easy to infer tool purpose from the name.

Tool Count4/5

With 44 tools, the server is quite comprehensive, covering a wide range of ENS operations. While this exceeds the typical 3-15 tool count, the scope of the domain (marketplace, registration, agent identity, etc.) justifies the number, and tools are well-organized into logical groups.

Completeness5/5

The tool surface covers the full lifecycle of ENS names: registration, renewal, wrapping, transfers, marketplace actions (listings, offers, purchases), record management, subnames, agent identity, and market intelligence. No obvious gaps are present for an ENS intelligence platform.

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