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Name Whisper — ENS Intelligence Layer

by ai.namewhisper

get_agent_reputation

Read-only

Check if an ENS name or wallet is a registered AI agent. Returns ENSIP-25 agent-registration verification (text record bindings between ENS names and on-chain agent registries), AI metadata from text records, ERC-8004 identity + reputation data, and ERC-8217 binding status (whether the agent identity is bound to — and transfers with — the ENS name's token).

ENSIP-25 verification is live: reads agent-registration text records from the name's resolver to confirm the ENS name ↔ registry binding, then resolves each bound agentId against the canonical ERC-8004 Identity Registry.

Reputation uses the live v1 feedback model: per-client feedback aggregated on-chain via getSummary. Note the unfiltered client set is Sybil-able — treat scores as a signal, not ground truth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameOrWalletYesENS name (e.g. "agent.eth") or wallet address (0x...) to look up

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description adds value by detailing the data retrieved and limitations (e.g., Sybil-able scores). It does not contradict 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 a clear front-loaded purpose, but the technical details make it slightly lengthy. It earns most sentences, though minor redundancy exists.

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?

Without an output schema, the description compensates by listing all key returns (ENSIP-25, ERC-8004, ERC-8217, reputation). It covers the complexity comprehensively.

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 coverage is 100% with a clear description of the single parameter. The description does not add significant meaning beyond the schema, so baseline 3 applies.

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 checks if an ENS name or wallet is a registered AI agent and returns specific data types. It distinguishes from siblings like search_agent_directory by focusing on reputation and binding status.

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

Usage Guidelines3/5

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

The description explains what the tool checks (registration, metadata, reputation), but does not explicitly state when to use this tool versus alternatives. It mentions reputation limitations but lacks explicit when-not guidelines.

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