Loading ToolBench
AI-powered autonomous payment agent for Cronos with conditional execution and market-aware logic
CronoPay has 16 tools with reasonable naming (verb-first convention mostly followed) and descriptions present for all tools. However, critical gaps emerge: input schemas are visible but lack comprehensive parameter descriptions and type constraints. Many parameters are documented at a surface level without format guidance, ranges, or validation rules. Error handling is minimal, most tools return generic success/failure without recovery guidance. Output schemas are not documented. The server mixes read-only and write operations without clear permission boundaries or confirmation patterns for destructive actions (e.g., transferToken, batch_transfer, cancel_pending_transaction). Tool composition is reasonable but some tools (e.g., create_execution_plan, visualize_plan) appear to be AI-orchestration wrappers rather than direct API calls, making their actual behavior opaque.
Analyze a transaction intent and assess its risk level. Returns risk assessment with explanation.
Execute batch token transfers to multiple recipients in a single operation.
Cancel a pending transaction by sending a 0-value transaction with the same nonce and higher gas. If nonce is not provided, cancels the oldest pending transaction.
Check the balance of an ERC20 token in a wallet on Cronos Testnet.
Generate an AI-powered execution plan for a payment intent. Analyzes the request, identifies required steps, evaluates risks, and creates conditional logic.
Decode and analyze a transaction by its hash.
Destructive operations (transferToken, batch_transfer, cancel_pending_transaction) lack confirmation/dry-run patterns. No tool description warns of irreversible consequences or suggests simulation first.
Parameter descriptions lack format guidance and constraints. E.g., 'amount' in transferToken has no range, decimal precision, or validation rule. 'address' parameters lack format specification (0x prefix, length). LLMs cannot infer valid input ranges.
Output schemas are not documented. Tools return JSON responses but LLMs have no formal schema to understand field types, nesting, or required fields. Clients must infer structure from examples.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 59 | 2025-06-18+ | v2 |
Estimate total gas cost for a batch transfer operation.
Estimate gas cost for a contract function call.
Retrieves the balance of an ERC20 token for a wallet address on Cronos Testnet (chainId: 338). Returns balance in human-readable format and raw format.
Get a spending summary for an address over a specified number of days.
Inspect a smart contract on Cronos Testnet. Returns contract info, functions, and events.
Query transaction history for an address with filtering options.
Call a read-only function on a smart contract (view/pure functions).
Simulate a token transfer without executing it. Shows gas costs, balance changes, and risk assessment.
Transfers USDC (devUSDC.e) tokens on Cronos Testnet (chainId: 338). This tool uses the verified USDC ERC-20 contract at 0xc01efAaF7C5C61bEbFAeb358E1161b537b8bC0e0. The contract address is hardcoded and validated server-side. Network: Cronos Testnet. Token: devUSDC.e (6 decimals). Contract: 0xc01efAaF7C5C61bEbFAeb358E1161b537b8bC0e0
Generate visual representation of an execution plan. Returns HTML, Mermaid diagram, or ASCII flow chart.
Error handling is generic. Tools return {success: false, error: message} without recovery guidance. No indication of whether errors are retryable, user-fixable, or fatal. LLMs cannot decide next steps.
Tool composition mixes orchestration (create_execution_plan, visualize_plan) with direct API calls. Orchestration tools delegate to LLM/AI internally, making their behavior opaque to the MCP client. Unclear whether these are deterministic or stateful.