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chain_ens_resolve

$0.005 via x402: resolve ENS in either direction on Ethereum — pass an ENS name (vitalik.eth) to get its 0x address, or pass a 0x address to get its primary ENS name (and avatar when set). The identity read every wallet, payment and UX agent makes to verify who it's sending to, or to display a human-readable name instead of a raw hex address. Live ENS registry; one paid call instead of running your own resolver.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoENS name to resolve to an address, e.g. vitalik.eth
addressNo0x address to reverse-resolve to its primary ENS name
x_paymentNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the full transparency burden. It discloses that this is a live ENS registry, that the call costs $0.005 and is paid via x402, that resolution works in both directions, and that the avatar is returned only when set. It does not describe failure modes or behavior for names/addresses with no ENS mapping, but it provides substantial and accurate behavioral context.

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 tightly written and front-loaded. The first sentence states the full functionality with examples, the second sentence explains the practical use case, and the third sentence adds data-source and payment context. Every sentence contributes to the agent's understanding without repeating schema information.

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 there is no output schema and no annotations, the description covers the important parts: what inputs do, what outputs to expect in both directions, the cost/payment model, the live registry source, and the intended use case. It could be more complete with explicit behavior for invalid names or addresses without a reverse record, but overall it is sufficiently complete for a simple resolver-style tool.

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 67%: name and address already have descriptive schema text, and the description adds examples and directional semantics. However, the x_payment parameter is not described in the schema, and the description only hints at it through '$0.005 via x402' without explaining how to set the parameter. The description also does not state explicitly that exactly one of name or address should be supplied.

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 first sentence clearly specifies the action: resolve ENS in either direction on Ethereum, with exact examples for both name-to-address and address-to-name. It is specific about the resource (Ethereum ENS registry) and distinguishes itself from sibling chain_* tools by covering bidirectional ENS resolution plus avatar support.

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 gives a concrete use case: the identity lookup that wallet, payment, and UX agents perform to verify destinations or display human-readable names instead of raw hex addresses. It also frames this as a paid alternative to running your own resolver, which helps an agent decide when to invoke the tool. It does not explicitly name alternatives or state when not to use it, but the context is clear.

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

C2.7/5.0
Disambiguation2/5

Many tools occupy the same conceptual space: web_scrape vs markdown_web_scraper, post_check vs brand_ai_visibility_check, llm_chat_completions vs post_api_v1_chat_completions, chain_transaction_status vs chain_confirmations, and connect_token vs token_security_check + dex_token_data. Descriptions help in places, but for an agent facing 92 tools these near-overlapping endpoints will frequently cause misselection.

Naming Consistency2/5

Everything is snake_case, but the conventions diverge sharply: get_chain_* and chain_* coexist for the same RPC family, post_* names are HTTP-route artifacts, api_generate reverses noun_verb order, and many names are bare nouns rather than verb_noun. There is no predictable naming pattern an agent can rely on.

Tool Count1/5

At 92 tools this is far beyond the range where an agent can keep the surface coherent, even for a store. The flat tool list mixes products, bundles, aliases, proxies and single-use verticals, so most of the count is noise for any given task. A catalog/search/payment model with fewer exposed tools would fit the storefront purpose better.

Completeness3/5

The server has impressive breadth and covers key storefront/market workflows: catalog, samples, credits, directory listing, notary, and the task lifecycle. But each domain is shallow: there is no chain transaction broadcast, no task update/cancel/dispute, no AI-visibility history, and many verticals are a single tool with no follow-on operation. The surface is broad but not deeply complete.