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Nitrostack-HAK

Fraud Alert MCP Server

update_fraud_rule

Deploy new fraud detection rules instantly to counter emerging threats. Define conditions, actions, and time-to-live for automated rule enforcement.

Instructions

Allows the AI to dynamically deploy new fraud detection rules based on emerging attack vectors

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to take when rule is triggered
ruleNameYesName of the fraud rule
ttlHoursYesTime-to-live in hours for the rule
conditionYesCondition for the rule (e.g., "amount > 5000 AND country != US")
Behavior2/5

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

With no annotations, the description must explain behavioral traits. It only states it deploys new rules, implying mutation, but does not disclose side effects (e.g., whether old rules are disabled, if rules are active immediately, or any authorization requirements). The behavioral information is insufficient.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it lacks structure (e.g., separate sections for purpose and behavior). Although short, it misses opportunities to be more informative without becoming verbose.

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?

Given the complexity of a mutation tool that deploys rules (4 required params, no output schema), the description is too minimal. It does not explain return values, effects on existing rules, or how the rule is evaluated. The description leaves significant gaps for an AI agent.

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 covers all 4 parameters with descriptions (100% coverage). The description adds context about 'emerging attack vectors' but no additional detail on parameter usage or semantics beyond the schema. Baseline 3 is appropriate since schema does the heavy lifting.

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?

Description clearly states it allows deploying new fraud detection rules, distinguishing it from sibling tools focused on transactions and user profiles. However, the verb 'deploy' and the resource 'fraud detection rules' are clear, but the name 'update_fraud_rule' suggests modification while description says 'deploy new', causing slight ambiguity.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. There is no mention of prerequisites, scenarios, or when not to use it. Sibling tools like analyze_transaction or flag_transaction_status could be relevant but no comparison is provided.

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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