Pre-flight check on a Base mainnet address before you pay it: contract vs EOA, ETH and USDC balances, outbound tx count, and warnings about whether funds sent there can actually be moved. Costs $0.002 per call, paid in USDC over x402 on Base. Calling this tool returns the payment requirements; failed calls are never billed.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Base mainnet address (0x-prefixed, 20 bytes) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses costs ($0.002 per call), payment method (USDC over x402), and the fact that it returns payment requirements. It also explains failed calls are never billed762. This is strong behavioral disclosure beyond what structured fields would provide.
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?
The description is concise, with the purpose front-loaded in the first clause. It uses a few sentences and includes essential details without fluff.
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 single-parameter tool, the description covers purpose, cost, billing, and output (payment requirements). It's complete enough for an agent to understand when and how to invoke it, and what to expect. No output schema, but it mentions the key output.
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 one parameter 'address' with 100% description coverage (0x-prefixed address). The tool description also mentions 'Base mainnet address', but adds little beyond the schema. Baseline 3 is appropriate; schema already covers parameter meaning.
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 clearly states the tool's purpose: 'Pre-flight check on a Base mainnet address before you pay it' and enumerates specific checks (contract vs EOA, balances, tx count, warnings). This is a specific verb+resource with concrete scope, distinguishing it from siblings like base_contract_type or base_balance.
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 description explicitly states when to use: 'before you pay it' – a clear usage context. It also mentions costs and payment requirements. However, it does not explicitly contrast with sibling tools like base_tx_check or base_portfolio, so it's missing explicit alternatives/exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct concern: address pre-flight, allowance, contract audit, contract type, gas, portfolio, prices, tx status. Even the two pricing tools are clearly separated (Chainlink ETH/BTC vs. any token via Uniswap V3), so selection ambiguity is minimal.
All tools share the base_ prefix and snake_case, which is highly predictable. However, the pattern mixes noun-style names (base_allowance, base_gas, base_token) with verb-including names (base_simulate_transfer, base_tx_check), so it is not a pure verb_noun convention throughout.
Twelve tools is a well-scoped set for a Base-focused on-chain analytics server. Each tool provides a meaningful capability without bloating the surface, and the free demo tool is a sensible inclusion.
The server covers the main read/analytics lifecycle: address checks, contract verification, token metadata, pricing, gas, portfolio, allowances, simulation, and transaction confirmation. Minor gaps exist, such as no generic contract-state reader or non-synthetic historical deep dives, but the core domain is well served.