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CarbonCashmere

Carbon Cashmere MCP Server

Official

post_v1_safety_check_standard

Analyze messages and transactions with AI-powered fraud detection, providing higher-confidence verdicts and clear reasoning traces for critical decisions like onboarding or approving transfers.

Instructions

Carbon-Guard Safety-Check (Standard): everything in Quick plus AI-powered fraud analysis for higher-confidence verdicts and a clear reasoning trace. Best when a decision actually matters — onboarding a counterparty, approving a transfer, vetting a suspicious message. Price: $1.00. Category: general.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, so description must disclose behavioral traits. It mentions AI-powered analysis, higher-confidence verdicts, and reasoning trace, but fails to explain how the tool is invoked (no parameters, no request body guidance), whether it is destructive, rate limits, or what happens on fraud detection. The lack of input schema explanation is a significant gap.

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

Conciseness5/5

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

Extremely concise: two sentences, price, and category. Every word adds value. Front-loaded with tool name and core capability. No fluff.

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

Completeness2/5

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

Despite no parameters and no output schema, the description leaves critical gaps: it does not explain how to supply the item to check (e.g., request body requirements), and it references 'Quick' without defining it. An agent cannot reliably invoke this tool without additional context about the request structure.

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

Parameters4/5

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

Input schema has zero parameters, so baseline is 4. Description does not need to explain parameters. However, it could clarify that the tool uses the request body for input, but since schema is empty, it's acceptable. No contradictions.

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

Purpose5/5

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

The description clearly states the tool performs a safety check with AI-powered fraud analysis, positioning it as the 'Standard' tier above 'Quick'. It lists specific use cases (onboarding counterparty, approving transfer, vetting suspicious message), effectively distinguishing from siblings like post_v1_safety_check (likely Quick) and post_v1_safety_check_deep.

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?

Explicitly indicates when to use: 'Best when a decision actually matters' with concrete examples. Implies Quick is for less critical decisions, but does not address other siblings like Deep, Batch, or Token, leaving some ambiguity. Still, the guidance is clear enough for high-stakes scenarios.

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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