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Riley Craig x402 Agent Store

by io.github.rccola990-cloud

chain_block_header

$0.09 via x402: the full header of any block — timestamp and age, transaction count, gas used vs limit with a utilization ratio and congested flag, base fee in gwei, miner and parent hash. /chain/block-number says WHERE the chain is; this says WHEN that block happened and how contested it was. Accepts a height or latest/finalized/safe. Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNobase|ethereum|optimism|arbitrum|polygon|gnosis (default base)
numberNoBlock height (decimal or 0x hex) or latest|finalized|safe|earliest (default latest)
x_paymentNo

Schema Changelog

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

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the price ($0.09 via x402), the output granularity (full header fields), and accepted input forms. It does not mention failure modes or rate limits, but for a read-only chain data endpoint, the disclosed details are solid.

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 dense with useful information—price, payload fields, differentiation, accepted inputs, chains—without unnecessary words. The structure front-loads the value proposition and the contrast with the sibling tool is concise.

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 lack of an output schema, the description compensates by enumerating the output fields. It also specifies supported chains and input formats. The only gap is not explaining the x_payment parameter, but the price mention partially covers its purpose.

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?

The schema already describes chain and number, but the description adds meaningful semantics by explaining the conceptual relationship to block number and reinforcing accepted values. It does not address x_payment, which slightly lowers the score from a 5.

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 the tool provides 'the full header of any block' and lists the specific fields returned. It also distinguishes itself from the sibling chain_block_number tool by contrasting 'WHERE the chain is' with 'WHEN that block happened and how contested it was'.

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?

The description explicitly contrasts this tool with get_chain_block_number, giving a clear when-to-use alternative. It also specifies accepted inputs (height or latest/finalized/safe) and supported chains, leaving no ambiguity about usage context.

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.

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