Parse x402 payment receipts into structured JSON. Returns amount, payer, receiver, chain, and timestamp. Pay 0.01 USDC per call on Base mainnet.
Scored across 1 tool
With only one tool, there is no possibility of overlap or misselection; the tool's purpose is unambiguous.
The single tool name follows a clear snake_case verb_noun pattern (extract_receipt), which is consistent with common conventions.
One tool is borderline thin for a server, even a focused one; while it matches the narrow purpose, it offers no additional operations or options.
For the stated domain of receipt field extraction, a single extraction tool fully covers the essential operation; no CRUD or lifecycle gaps are apparent.
Extract structured fields (merchant, date, currency, total, tax, line_items) from receipt text.
| Name | Required | Description | Default |
|---|---|---|---|
| document | Yes | Raw receipt text — paste the full receipt as plain text. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden. It helpfully enumerates the output fields, which is meaningful since there is no output schema, but it omits any statement about read-only nature, accuracy, handling of missing fields, or return format.
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?
A single, front-loaded sentence with zero wasted words. The purpose and output fields are stated immediately, making it easy to scan and parse.
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 simple one-parameter extraction tool with no output schema, the description does a good job of listing the extracted fields, compensating for the missing output schema. It stops short of describing field formats (e.g., line_items structure) or edge-case behavior, but is largely complete.
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?
Schema description coverage is 100%, so the single 'document' parameter is fully documented in the schema ('paste the full receipt as plain text'). The description adds no extra parameter meaning beyond what the schema already provides, so the baseline of 3 applies.
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 states a specific verb (Extract) and resource (structured fields from receipt text), and enumerates the exact fields returned (merchant, date, currency, total, tax, line_items). There are no sibling tools, so no differentiation is needed; the purpose is unambiguous.
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?
It does not say when to use this tool versus alternatives, nor does it state prerequisites or exclusions (e.g., 'use only with raw text, not images'). Usage is inferable only from the purpose statement, which is minimal guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
extract_receipt
Add one secure layer between your agents and this server.