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Name Whisper — ENS Intelligence Layer

by ai.namewhisper

search_knowledge

Read-only

Search the ENS knowledge base — governance proposals, protocol documentation, developer insights, blog posts, forum discussions, and Farcaster casts from key ENS figures (Vitalik, Nick Johnson, etc.). Powered by semantic search over curated ENS sources.

USE THIS (don't answer from memory) for any "how does X work" / "what is X" / "why does ENS …" PROTOCOL-MECHANICS question — renewal, the grace period, the premium/temporary-premium auction, registration & commit-reveal, resolvers, subnames, the NameWrapper & fuses, reverse resolution, ENSv2 — plus ENS history, DAO/governance proposals, community sentiment, and "what did say about ". Mechanics questions feel answerable from general knowledge, but a sourced, citable answer is the bar here — search first, then cite what you find.

Do NOT use this for name valuations, market data, availability, or a specific name's live status — use the other tools for those.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results to return (default 6)
queryYesSearch query — what you want to know about ENS governance, protocol, ecosystem, or history
sourceNoFilter to a specific source. Omit to search all sources.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark the tool as read-only (readOnlyHint: true). The description adds context that it uses semantic search over curated sources, which is consistent. No destructive behavior is implied. The description 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a single sentence stating purpose followed by clear usage guidance in the next paragraph. Every sentence adds value, and it avoids verbosity.

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 the tool's complexity (semantic search over multiple sources), read-only annotation, and no output schema, the description provides sufficient context: what it searches, how to use it, and what not to use it for. A minor gap is the lack of mention about data freshness or limitations, but overall it's complete.

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 has 100% description coverage with reasonable descriptions for all three parameters (query, limit, source). The description adds minimal extra meaning beyond what the schema provides, but it reinforces usage context. Baseline for high coverage is 3.

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 it searches the ENS knowledge base across multiple curated sources (governance proposals, docs, blog, forum, Farcaster). It distinguishes itself from sibling tools like 'search_ens_names' by focusing on knowledge content rather than name lookups.

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?

Explicitly tells when to use the tool ('for any 'how does X work' / 'what is X' / 'why does ENS …' protocol-mechanics question') and provides a detailed list of example queries. Also clearly states when NOT to use it ('Do NOT use this for name valuations, market data, availability, or a specific name's live status') and directs to other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Name Whisper — ENS Intelligence Layer toolsInspect
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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