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Compare human instruction and agent interpretation — $0.001

prepare_interpretation_delta_purchase
Read-only

Machine-native checks from $0.001 USDC per successful execution. No subscription required for S0.1 primitives. Browse the $0.001 primitive catalog. Create a purchase intent and pay only when /market.primitive_entry.paid_execution_enabled is true; otherwise paid execution is unavailable. Prepare a machine-payable x402 request. Check whether an agent's current interpretation materially differs from the original human message. Bounded instruction comparison: exact text equality or explicit boolean and permission polarity mismatch. Binary 0/1 when decidable; abstains before billing otherwise. Current deterministic scope: exact normalized text equality returns 0; true/false, yes/no, enabled/disabled, present/absent, required/not required and allowed/not allowed return 1. Other inputs abstain before billing. This is not general language interpretation, diagnosis or a similarity score.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "HUMAN_MESSAGE": "<HUMAN_MESSAGE>",
      "CURRENT_INTERPRETATION": "<CURRENT_INTERPRETATION>"
    },
    "name": "prepare_interpretation_delta_purchase"
  }
}

Input Schema

NameRequiredDescriptionDefault
HUMAN_MESSAGEYes
CURRENT_INTERPRETATIONYes

Output Schema

NameRequiredDescriptionDefault
methodYes
endpointYes
price_usdYes
request_bodyYes
payment_protocolYes
required_headersYes
purchase_intent_methodYes
purchase_intent_endpointYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations only declare readOnlyHint and openWorldHint; the description adds genuinely new behavioral context: the billing gate, pre-billing abstention, binary 0/1 outcome, and the exact deterministic decision scope (normalized text equality → 0; boolean/polarity pairs → 1). It does not explain what the caller receives on abstention, but the output schema covers return values. Minor tension: 'Create a purchase intent and pay' reads like a write while readOnlyHint=true, though 'prepare ... request' is plausibly read-only, so this is not a clear contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first three sentences ('Machine-native checks from $0.001 USDC...', 'No subscription required...', 'Browse the $0.001 primitive catalog') are promotional filler that do not help an agent invoke the tool, and the actual purpose does not appear until mid-description. Pricing is restated multiple times and the scope enumeration is dense prose that would read better as a list.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and annotations plus description jointly cover safety, billing gating, abstention, and the decidable scope. The only real gap is caller-facing parameter formatting. For a two-string comparison primitive, the definition is complete enough to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for HUMAN_MESSAGE and CURRENT_INTERPRETATION. It partially does by defining the comparison space (normalized exact text equality, boolean/polarity mismatch), which implies how the two strings are interpreted. It still never specifies input format, normalization rules the caller must apply, or length constraints, so the compensation is incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description does state a specific verb and resource: 'Check whether an agent's current interpretation materially differs from the original human message,' plus 'Prepare a machine-payable x402 request.' That is enough for an agent to identify the operation. However, it never differentiates itself from the sibling prepare_state_deviation_purchase, and the purpose is buried behind three sentences of pricing boilerplate, leaving the tool's dual identity (payment prep vs. comparison) somewhat muddled.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit gating conditions ('pay only when ...paid_execution_enabled is true; otherwise paid execution is unavailable') and explicit exclusions ('not general language interpretation, diagnosis or a similarity score'), plus when-not behavior ('abstains before billing otherwise'). What is missing is any guidance about when to prefer this over prepare_state_deviation_purchase, so the alternative-selection dimension is absent.

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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