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chain_transaction_status

$0.008 via x402: look up any transaction by hash — confirmation status (success/failed/pending), block number, confirmations, value, from/to, fee paid, gas used, and decoded method. The read every settlement, trading and payment agent polls after sending a tx to confirm it landed. Across Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis. Live from Blockscout; one paid call instead of running your own RPC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hashYesTransaction hash (0x... 64 hex)
chainNobase|ethereum|optimism|arbitrum|polygon|gnosis (default base)
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

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It adds useful context: the exact cost ($0.008 via x402), that it is a read operation, the live data source (Blockscout), and supported networks. It does not cover rate limits, failure modes, or invalid-hash behavior, but for a simple read lookup it provides solid transparency.

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 compact and front-loaded, packing the core purpose, returned fields, use case, networks, source, and cost into four short sentences. It earns its length, though the second sentence contains a grammatical awkwardness ('The read every...') and the structure could be slightly cleaner.

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?

For a tool with 3 simple parameters and no output schema, the description covers the essentials: what it returns, which chains it supports, how it is paid for, and where the data comes from. It could be more complete by explaining x_payment and possible error conditions, but it is sufficient for a low-complexity lookup 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?

The schema already documents hash and chain, covering 67% of parameters, so the description does not need to repeat those basics. It adds value by explaining the hash-based lookup and supported chains, but it does not explain the undocumented x_payment parameter or connect the '$0.008 via x402' pricing to that parameter. Thus it stays at the baseline rather than rising above it.

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 names the action ('look up any transaction by hash') and the specific resource (transaction status by hash), while enumerating the returned fields: confirmation status, block number, confirmations, value, from/to, fee paid, gas used, and decoded method. It also frames the exact use case for settlement, trading, and payment agents, making it easy to distinguish from the many sibling chain tools.

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 provides clear context for when to use it: 'The read every settlement, trading and payment agent polls after sending a tx to confirm it landed.' It also gives practical guidance about using one paid call instead of running an RPC. However, it does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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.