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ComplianceCow

ComplianceCow MCP Server

prepare_applications_for_execution

Analyze rule tasks to determine application configuration requirements and identify if multiple tasks can share the same application.

Instructions

Analyze rule tasks and prepare application configuration requirements for execution.

This tool helps users understand what applications are needed and whether they can share applications across multiple tasks.

WHEN TO USE:

  • Before calling execute_rule() to understand application requirements

  • To identify if multiple tasks can share the same application

  • To determine if unique identifiers are needed when using different applications for same appType

NOTE: This tool is optional. Rules with only 'nocredapp' tasks can be executed directly without any application configuration. Use this tool only when tasks require credentials.

APPLICATION SHARING SCENARIOS (when applications are needed):

  1. Shared Application: User wants same credentials for all tasks of an appType

    • Single application config with basic appTags (just appType)

    • One application covers multiple tasks

  2. Separate Applications: User needs different credentials per task

    • Must add unique identifier key (e.g., "purpose") to task appTags

    • Each application config must include matching unique identifier

  3. No Application Needed: All tasks have 'nocredapp' appType

    • Skip application configuration entirely

    • Call execute_rule() with an empty applications list

WORKFLOW:

  1. Call this tool with rule_name

  2. Review which tasks need applications (if any)

  3. If no tasks need applications (all nocredapp): Skip to step 6

  4. For tasks with same appType, decide: share or separate?

  5. If sharing: Provide one application config per appType If separate: Add unique identifiers and provide separate configs

  6. Call execute_rule() with configured applications (or empty list for nocredapp rules)

Args: rule_name: Name of the rule to analyze

Returns: Dict with analysis results and configuration guidance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rule_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. It transparently describes the tool's behavior: analyzing tasks, identifying sharing possibilities, and guiding configuration. It also clarifies the optional nature.

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?

Well-structured with headings, bullets, and scenarios, but somewhat lengthy. Front-loaded with purpose and clear organization.

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

Completeness5/5

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

Given the simple input and output schema, the description covers all necessary context: when to use, scenarios, workflow, and return type. Adequately completes the picture 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?

Only one parameter 'rule_name' with 0% schema coverage. The description adds 'Name of the rule to analyze', which is minimal but adequate for a single string parameter.

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 analyzes rule tasks and prepares application configuration requirements for execution. It specifies the verb 'analyze' and 'prepare' and distinguishes from sibling tools like execute_rule.

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

Usage Guidelines5/5

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

Explicitly provides WHEN TO USE sections, including when not to use (optional for nocredapp tasks), and a detailed WORKFLOW with decision points.

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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