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Name Whisper — ENS Intelligence Layer

by ai.namewhisper

search_agent_directory

Read-only

Search the AI agent directory — find registered agents by name, capability, protocol support, or reputation. Powered by the live ERC-8004 registry via 8004scan (110,000+ agents indexed across 50+ chains).

Returns agent identity, owner wallet/ENS, reputation scores, supported protocols (MCP/A2A/OASF), verification status, and links to 8004scan profiles.

Examples:

  • "trading agents on Base" → search for trading agents filtered to Base chain

  • "MCP agents" → find agents that support the Model Context Protocol

  • "high reputation agents" → set minReputation to find top-scored agents

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoFilter by chain name (e.g. "Ethereum Mainnet", "Base", "Solana Mainnet")
limitNoMax results (default 25, max 50)
queryNoSearch query — agent name, capability, or description
capabilitiesNoFilter by supported protocols (e.g. ["MCP", "A2A", "OASF"])
minReputationNoMinimum total score (0-100)

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true. Description adds that it queries a live registry via 8004scan with 110,000+ agents indexed across 50+ chains, providing useful behavioral context beyond the annotation. No contradictions.

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?

Concise and front-loaded: first sentence states purpose, second describes return values, then bulleted examples. No unnecessary words, every sentence 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?

No output schema, but description clearly lists returned fields (agent identity, owner, reputation, protocols, verification status, links). Given the tool's moderate complexity and 5 parameters, the description is sufficient for effective use.

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?

Input schema covers 100% of parameters with individual descriptions. The description adds usage examples and context (e.g., 'minReputation' tied to 'top-scored agents') but does not add new semantic meaning beyond what the schema already provides. Baseline 3 due to high schema coverage.

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?

Description clearly states 'Search the AI agent directory' with specific verb and resource. It distinguishes from sibling tools like search_ens_names and search_knowledge by focusing on agents, capabilities, protocols, and reputation. The examples further clarify the purpose.

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?

Provides explicit when-to-use: searching for registered agents. Implicitly excludes ENS names and knowledge searches, which are handled by siblings. Examples show filtering by chain, protocol, and reputation, guiding appropriate queries.

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