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Name Whisper — ENS Intelligence Layer

by ai.namewhisper
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get_market_activity

Read-only

Get recent ENS marketplace activity. Covers exactly three event types — SALE, PREMIUM_REGISTRATION and SWAP — and nothing else: it does NOT report listings, standing offers, mints, transfers, renewals or burns, so never conclude from an empty result that none of those occurred. Returns event details including name, price (in ETH), buyer/seller addresses, and timestamp. Sorted by most recent first. Pass collection (a slug such as "10k-club" or "999-club") to scope to one club — an unscoped call is the entire market, so never present unscoped results as a collection's sales. Not every row is a sale: check type before describing one as such. PREMIUM_REGISTRATION is a Dutch-auction registration from the ENS premium decay, NOT a secondary-market sale, so never quote it as evidence of what a name sold for; SWAP is a name-for-name trade and has no price. SALE includes accepted offers. This is raw activity only — it makes NO wash-trading / authenticity judgment; for "is this wash trading / fake volume?" use wash_check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 25, max 100)
offsetNoPagination offset
collectionNoRestrict to names in one collection, by slug — e.g. "10k-club", "999-club", "3-letter-dictionary". Use it whenever the user names a club or collection; without it the results are the WHOLE market and must never be described as a collection's sales.
eventTypesNoFilter by event type. Defaults to all three; see the tool description for what each means.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / collection
      Added value: +{
+  "description": "Restrict to names in one collection, by slug — e.g. \"10k-club\", \"999-club\", \"3-letter-dictionary\". Use it whenever the user names a club or collection; without it the results are the WHOLE market and must never be described as a collection's sales.",
+  "type": "string"
+}
  2. Changed8 schema fields changed
    • changedInput schema / properties / eventTypes / description
      Previous value: -"Filter by event type(s). Defaults to all types."New value: +"Filter by event type. Defaults to all three; see the tool description for what each means."
    • changedInput schema / properties / eventTypes / items / enum
      Previous value: -[
-  "SALE",
-  "LISTING_CREATED",
-  "OFFER_CREATED",
-  "MINT",
-  "TRANSFER",
-  "RENEWAL",
-  "BURN"
-]New value: +[
+  "SALE",
+  "PREMIUM_REGISTRATION",
+  "SWAP"
+]
    • addedInput schema / properties / limit / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / limit / minimum
      Added value: +1
    • changedInput schema / properties / limit / type
      Previous value: -"number"New value: +"integer"
    • addedInput schema / properties / offset / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / offset / minimum
      Added value: +0
    • changedInput schema / properties / offset / type
      Previous value: -"number"New value: +"integer"
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only indicate readOnlyHint, but the description goes far beyond: it explains sort order, returned fields, type-specific semantics (PREMIUM_REGISTRATION is not a secondary-market sale, SWAP has no price), and the tool's lack of wash-trading judgment. 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.

Conciseness5/5

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

Though dense, every sentence earns its place by clarifying interpretation pitfalls rather than repeating schema content. The core purpose is front-loaded, and caveats are organized logically around event types and scoping.

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?

With no output schema, the description still tells the agent what fields are returned, that rows are sorted most-recent-first, and how to interpret each event type. Combined with the schema for pagination and the readOnly annotation, nothing essential is missing for correct invocation.

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%, so the baseline is 3. The description adds important semantics for collection (scoping to one club vs. whole market) and for eventTypes (what each event type means), while limit and offset are adequately handled by the schema.

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 uses a specific verb and resource ('Get recent ENS marketplace activity') and immediately narrows scope to exactly three event types: SALE, PREMIUM_REGISTRATION and SWAP. It explicitly excludes listings, offers, mints, transfers, renewals and burns, making it easy to distinguish from related market tools.

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?

Gives explicit guidance on when to pass the collection parameter and warns that unscoped results represent the whole market and must not be presented as a collection's sales. It also names wash_check as the alternative when the user is asking about wash trading or fake volume.

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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