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TradePilot Agent Commerce

Account research plan

tradepilot_service_account_research_questions
Destructive

Create a public-business research checklist and source plan; do not claim the research has been performed. Uses buyer-supplied information only; no external research or outbound actions. Returns a draft for human review. Price: 0.25 USD. Payment requires explicit wallet authorization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes
result_expiresNo
idempotency_keyNo
result_signatureNo
payment_signatureNo

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 declare readOnlyHint=false, destructiveHint=true, and openWorldHint=true. The description adds important behavioral context: it does not perform external research, uses only buyer-supplied info, returns a draft for human review, and requires payment with explicit wallet authorization. This goes beyond the annotations and clarifies the destructive/payment nature. No contradiction with annotations.

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

Conciseness4/5

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

The description is three sentences, front-loaded with the core purpose and key constraints. It includes pricing and payment authorization, which are essential. It's concise and each sentence adds value, though the payment details could arguably be in annotations or structured fields.

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

Completeness3/5

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

The description covers the tool's purpose, constraints, and payment requirement, but with no output schema and 0% parameter coverage, it leaves the agent without guidance on what the draft output looks like or how to fill the required parameters. The description is adequate for basic selection but incomplete for correct invocation without schema inspection.

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

Parameters2/5

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 explaining parameters. The description mentions 'buyer-supplied information' and 'source_text' implicitly, but it doesn't explain the key parameters: brief, source_text, audience, result_expires, idempotency_key, result_signature, payment_signature. The description does not map to the schema fields, leaving the agent to infer what 'brief' and 'source_text' mean. This is a significant gap given 0% coverage.

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 clearly states the tool creates a research checklist and source plan, and explicitly notes it does not perform research. It distinguishes itself from research-performing tools by stating 'do not claim the research has been performed' and 'no external research or outbound actions.' However, it doesn't explicitly name a sibling alternative, so it's clear but not fully differentiated.

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?

The description provides clear context: it uses buyer-supplied information only, no external research, and returns a draft for human review. This implies when to use it (when a research plan is needed, not actual research) and when not to use it (when research execution is needed). It doesn't explicitly name alternatives, but the constraints are explicit enough to guide selection.

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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