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QuickBuild agent tools (x402)

Base gas price and tx cost

base_gas_price
Read-only

[PAID $0.001 USDC per call via x402 on Base; errors are free] Live gas snapshot for Base mainnet (chain 8453) read from public Base RPC: latest block number/time/utilization, base fee, eth_gasPrice, eth_maxPriorityFeePerGas, the last 10 blocks of base fees, slow/standard/fast EIP-1559 fee suggestions (10th/50th/90th percentile tips) in gwei and wei, and the estimated total cost (L2 execution + OP Stack L1 data-fee upper bound) of an ETH transfer, an ERC-20 transfer and a swap in ETH and USD (Chainlink ETH/USD on Base). No params. Cached 4 s. Errors are never charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses the x402 pricing model ($0.001 USDC per call), that errors are never charged, the data source (public Base RPC), the oracle used for USD conversion (Chainlink ETH/USD on Base), the 4 s cache, and even the composition of the cost estimate (L2 execution + OP Stack L1 data-fee upper bound). This is exactly the operational context an agent needs before paying for a call.

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?

Front-loaded with the two things that most affect an agent's decision: the price and that errors are free. The remainder is one long enumerative sentence listing returned fields; it is dense but nearly every clause maps to a concrete output, so little is wasted.

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 carries the full burden of describing return values and does so comprehensively, field group by field group. Combined with the pricing, caching and read-only annotation context, an agent has everything needed to call this correctly.

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, which is the baseline-4 case. The description confirms this explicitly ('No params'), so nothing is left ambiguous, though there are no parameters whose meaning could be enriched further.

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?

States a specific verb+resource ('Live gas snapshot for Base mainnet (chain 8453)') and enumerates exactly what is returned: block number/time/utilization, base fee, eth_gasPrice, priority fee, fee history, percentile-based slow/standard/fast suggestions, and transfer/swap cost estimates. That level of specificity distinguishes it from siblings like base_token_info or base_tx_status without opening any schema.

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?

Usage is implied by the content (gas estimation for ETH transfers, ERC-20 transfers and swaps on Base mainnet chain 8453), and 'No params' plus the 4 s cache tell the agent it can call it blindly and repeatedly. However, there is no explicit when-to-use/when-not guidance and no routing to or from sibling tools, so an agent must infer the 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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