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ComplianceCow

ComplianceCow MCP Server

fetch_dashboard_framework_controls

Retrieve detailed control-level data for a specific Common Control Framework and review period. Returns assignment status, compliance state, due dates, scores, and priority levels with pagination support.

Instructions

Function Overview: Retrieve Control Details for a Given CCF and Review Period

This function retrieves detailed control-level data for a specified Common Control Framework (CCF) during a specific review period.

Args:

  • review_period: The compliance period (typically a quarter) for which the control-level data is requested.
    Format: "Q1 2024"

  • framework_name:
    The name of the Common Control Framework to fetch data for.

Purpose

This function is used to fetch a list of controls and their associated data for a specific CCF and review period.
It does not return an aggregated overview — instead, it retrieves detailed, item-level data for each control via an API call.

The results are displayed in the MCP host with client-side pagination, allowing users to navigate through the control list efficiently without making repeated API calls.

Returns: - controls (List[FramworkControlVO]): A list of framework controls. - name (str): Name of the control. - assignedTo (str): Email ID of the user the control is assigned to. - assignmentStatus (str): Status of the control assignment. - complianceStatus (str): Compliance status of the control. - dueDate (str): Due date for completing the control. - score (float): Score assigned to the control. - priority (str): Priority level of the control. - page (int): Current page number in the overall result set. - totalPage (int): Total number of pages. - totalItems (int): Total number of items. - error (Optional[str]): An error message if any issues occurred during retrieval.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodYes
framework_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
controlsNo
pageNo
totalPageNo
totalItemsNo
errorNo
Behavior4/5

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

Discloses client-side pagination behavior and clarifies the API retrieves detailed rather than summary data, adding context beyond the null annotations.

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?

Well-structured with clear sections, but overly verbose in documenting return values (controls list, page, totalPage, etc.) that should be delegated to the existing output schema.

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?

Adequate for simple 2-parameter tool but incomplete due to the parameter name mismatch and redundant return value documentation despite presence of output schema.

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?

Critical mismatch: description references 'review_period' but schema expects 'period'; while semantic descriptions are provided for both parameters, the naming discrepancy could cause invocation failures with 0% schema 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?

Clearly states it retrieves detailed control-level data (not aggregated) for a specific CCF and review period, though it doesn't explicitly name the sibling aggregation tool (fetch_dashboard_framework_summary).

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 states when to use (for detailed item-level data) and when not to use (does not return aggregated overview), but lacks specific alternative tool recommendations.

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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