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ARYSPHERE x402 chain reads and token verdicts

x402_chain_reads_v1__network_info_summary

Read-only

Base network data in one call.

GET https://api.arysphere.com/v1/ventures/x402_chain_reads_v1/network_info_summary. Same payment terms as that HTTP route. Call once with no payment. The result is the payment terms. Retry the same call with the signed payment at _meta["x402/payment"]. Measured output: {"chain": "base", "hex": {"eth_blockNumber": "0x3245954", "eth_chainId": "0x2105", "eth_gasPrice": "0x5b8d80"}, "method": "summary", "ok": true, "result": {"base_fee_per_gas_wei": 5000000, "block_gas_limit": 400000000, "block_gas_used": 33899437, "block_number": 52713812, "block_timestamp": 1792216971, "block_transactions": 190, "chain_id": 8453, "gas_price_wei": 6000000}, "service": "x402_chain_reads_v1.network_info_summary"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

readOnlyHint=true already declares the safety profile, yet the description adds genuinely non-obvious behavior: this is a paid x402 route, the first call returns payment terms rather than data, and a retry with a signed payment is required. That auth/payment-flow disclosure is exactly the kind of context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The payment protocol sentences are well front-loaded and earn their place. The raw 'Measured output' JSON blob is long and partly redundant (duplicated fields under both hex and result), consuming a large share of the text; a trimmed example would convey the same shape.

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?

With no output schema, the description correctly supplies a literal response sample so the agent knows the return shape, and it fully explains the payment handshake. Nothing critical is missing for calling it correctly, though error/retry-failure behavior is not covered.

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 tool takes zero parameters, so there is no per-parameter semantics for the description to document; baseline for a no-param tool applies. The only argument-like input (the _meta payment envelope) is explained, which is a modest bonus.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening line 'Base network data in one call' names the resource (Base-chain network summary) and the measured-output sample pins down exactly which fields come back (block number, base fee, gas price, chain id). It is clear, but it does not differentiate itself from close siblings such as network_info_balance_bundle or chain_fees_digest, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a precise operational protocol for the paid endpoint (call once with no payment to get terms, retry with the signed payment at _meta['x402/payment']), which is real usage guidance. It never states when to prefer this tool over sibling read tools, so the when/when-not dimension is only implied.

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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