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ComplianceCow

ComplianceCow MCP Server

by ComplianceCow
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

confirm_template_input

Confirm and process template inputs after user validation, uploading files or storing content in memory while automatically updating compliance rule configurations to advance the workflow.

Instructions

Confirm and process template input after user validation.

CONFIRMATION PROCESSING (Enhanced with Automatic Rule Updates):

  • Handles final confirmation of template content

  • Uploads files for FILE dataType inputs

  • Stores content in memory for non-FILE inputs

  • MANDATORY step before proceeding to next input

  • NEW: Automatically updates the rule with new input after processing

  • Skips confirmation if the user accepts the suggested template

PROCESSING RULES (Enhanced):

  • FILE dataType: Upload content as file, return file URL

  • HTTP_CONFIG dataType: Upload content as file, return file URL

  • Non-FILE dataType: Store content in memory

  • Include metadata about confirmation and timestamp

  • NEW: Automatic rule update with new input data

AUTOMATIC RULE UPDATE PROCESS: After successful input processing, this tool automatically:

  1. Fetches the current rule structure

  2. Adds the new input to spec.inputs

  3. Updates spec.inputsMeta__ with input metadata

  4. Calls create_rule() to save the updated rule

  5. Rule status will be auto-detected (DRAFT → collecting_inputs → READY_FOR_CREATION)

UI DISPLAY REQUIREMENT:

  • The file URL must ALWAYS be displayed to the user in the UI, allowing the user to view or download the file directly.

Args: rule_name: Descriptive name for the rule based on the user's use case. Note: Use the same rule name for all inputs that belong to this rule. Example: rule_name = "MeaningfulRuleName" task_name: Name of the task this input belongs to input_name: Name of the input parameter rule_input_name: Must be one of the values defined in the rule structure's inputs confirmed_content: The content user confirmed

Returns: Dict containing processing results (file URL or memory reference) and rule update status

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rule_nameYes
task_nameYes
rule_input_nameYes
input_nameYes
confirmed_contentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A3.9/5.0
Behavior5/5

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

Excellent disclosure of side effects: automatic rule updates (fetching structure, updating spec.inputs and spec.inputsMeta__, calling create_rule()), status transitions, FILE vs non-FILE handling, and UI display requirements.

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 headers but excessively verbose; repetitive 'Enhanced' and 'NEW' annotations bloat the text without adding semantic value.

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

Completeness4/5

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

Comprehensive coverage of complex automatic rule update process and UI requirements; brief return value summary is acceptable despite presence of output schema.

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?

Compensates effectively for 0% schema coverage by providing detailed Args section with constraints (e.g., rule_input_name must match rule structure values, rule_name consistency requirement) and examples.

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 confirms and processes template input after validation, distinguishing it from parameter confirmation via 'template' specificity, though explicit contrast with confirm_parameter_input is absent.

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

Usage Guidelines3/5

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

Identifies it as a 'MANDATORY step' and notes skipping conditions (user accepts suggested template), but lacks explicit when/when-not guidance versus sibling tools like confirm_parameter_input.

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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