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Decian-Inc

curricula-mcp

by Decian-Inc

list_account_phishing_scenarios

Retrieve phishing scenarios for a specific account, with filtering, pagination, and sorting options to identify security awareness coverage.

Instructions

List phishing scenarios for an account. Calls GET /accounts/{accountId}/phishing-scenarios. Put route IDs in path_params and filtering, pagination, sorting, or include values in query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
queryNo
path_paramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only or mutating, what authentication or permissions are required, or whether results are paginated. It only indicates how to structure the request (route IDs in path_params, etc.) but no side effects or limitations. This is a significant gap for a listing operation.

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?

The description is concise and front-loaded: the first sentence states the purpose, the second provides the HTTP endpoint, and the third gives usage routing. Every sentence adds value, with no filler or redundancy. It is appropriately structured for quick agent scanning.

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 tool is a simple listing operation with an output schema that might cover return structure, and the description covers basic usage. However, it lacks behavioral context like pagination specifics, authentication, or error handling, which are important for an HTTP-based tool. The absence of annotations increases the need for such details, making the description only minimally adequate.

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%, and the schema has three parameters (body, query, path_params) with no property descriptions. The description attempts to compensate by explaining where to put route IDs (path_params) and filtering/pagination/sorting/include (query), which is helpful. However, it does not explain the 'body' parameter at all, leaving a third of the parameters undocumented. The partial guidance is insufficient to fully compensate for the lack of schema docs.

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 action: 'List phishing scenarios for an account.' It names the specific resource and the HTTP endpoint, and it differentiates from the sibling tools that list scenarios globally (list_phishing_scenarios) or for campaigns (list_phishing_campaign_scenarios), making the purpose precise and non-confusable.

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 guidance on when to use this tool by specifying the account scope, and it implicitly distinguishes from siblings that list scenarios for other scopes. However, it does not explicitly mention when NOT to use it or point to alternatives, so it lacks explicit exclusions. The context is clear enough for an agent to infer usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.