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Name Whisper — ENS Intelligence Layer

by ai.namewhisper

make_offer

Place an offer (bid) on a registered ENS name on NameWhisper via Seaport 1.6.

Returns an unsigned Seaport OrderComponents payload (plus EIP-712 domain/types) that the caller's wallet signs. The buyer offers WETH and receives the name on acceptance. After signing, POST { orderComponents, signature, label, orderType: 'offer', variant: 'nw' } to https://namewhisper.ai/api/orderbook/submit (authenticated) to store the offer in NameWhisper's orderbook — the owner sees it and can accept, counter, or decline.

Offers settle in WETH: the maker needs wrapped ETH and an approval for Seaport to spend it (the NameWhisper UI handles this approval automatically at signing time).

Fee structure: 1% marketplace fee baked into the order as a Seaport consideration item.

NW-native only — offers are not cross-posted to other marketplaces.

Tip: Use get_valuation first to understand fair market value before making an offer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesENS name to make an offer on (e.g. "coffee.eth")
currencyNoOffer currency. Seaport offers settle in WETH; ETH is treated as WETH.WETH
amountEthYesOffer amount in ETH (placed on-chain as WETH)
expiryHoursNoOffer expiry in hours (default: 72)
walletAddressYesYour wallet address (the offer maker / buyer)

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations, the description reveals behavioral traits: returns unsigned payload, requires user signing and external API submission, settles in WETH needing approval, includes 1% fee. No contradiction 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 with clear paragraphs, front-loads the main action, and each sentence adds value. Slightly lengthy but appropriate for the complexity, earning a 4.

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?

Despite lacking output schema, the description fully explains the return value (unsigned OrderComponents), subsequent steps, prerequisites (WETH, approval), and fee structure. Complete for a complex tool.

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?

With 100% schema coverage, the description adds value by explaining that ETH is treated as WETH, clarifying the wallet as buyer, and providing context for currency and expiry defaults, though schema already covers basics.

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 places an offer on a registered ENS name via Seaport 1.6, specifies the output (unsigned payload), and differentiates from sibling tools like accept_offer and cancel_offer by detailing the unique workflow and marketplace (NameWhisper).

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 provides a tip to use get_valuation first, explains the workflow (sign then submit), and notes fee structure and NW-native limitation. It lacks explicit when-not-to-use statements but offers sufficient context for appropriate use.

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.

Resources