Current Base gas price. $0.01 per call. Typically returns in under 2s.
Returns base fee, priority fee percentiles from the last 20 blocks, congestion read, and three recommended (slow/normal/urgent) fee tiers with ETH cost estimate.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses per-call cost, typical latency, and a detailed breakdown of the response content, which is more transparent than most definitions. This is particularly valuable for an agent estimating cost and runtime before invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences front-load the core purpose, then add cost and latency context, then enumerate return data. There is no filler or redundancy; every sentence contributes necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless query tool without an output schema, the description supplies essential behavioral and output information: pricing, latency, and the specific fields returned. Minor omissions like units (e.g., Gwei) and response format prevent a perfect score, but the tool remains fully understandable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and 100% schema coverage, so there are no parameter semantics to explain. The description appropriately focuses on output behavior rather than parameters, matching the baseline of 4 for parameterless tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the tool as returning the current Base network gas price and enumerates the specific data returned (base fee, priority fee percentiles, congestion read, fee tiers). It is clearly distinct from sibling tools targeting wallets, payments, tokens, services, or transaction simulation, though it lacks an explicit verb.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied: obtain the current gas price on Base. However, there is no explicit guidance on when to prefer this tool over alternatives or any exclusions, though the sibling tools are unrelated enough that ambiguity is low.
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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Each tool maps to a distinct concern: gas pricing, wallet inspection, token risk, transaction simulation, and service/payment meta-info. Even the two informational tools are cleanly separated by their purpose. No likely misselection.
Names mix verb_noun patterns like inspect_wallet and simulate_transaction with noun-based patterns like gas_price and service_info. All are readable and consistently snake_case, but there is no single predictable naming convention.
Six tools is a well-scoped size for a focused Base read-only lens service. Each tool serves a clear, non-redundant purpose.
The tool set covers the main Base workflows: gas pricing, wallet inspection, token risk screening, and transaction simulation. Missing transaction/block lookup and full portfolio enumeration are moderate gaps, but some are explicitly noted as indexer-dependent limitations.