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ComplianceCow

ComplianceCow MCP Server

verify_collected_inputs

Verify collected compliance inputs by displaying templates and parameters for user confirmation, then automatically finalize rule creation with I/O mapping.

Instructions

Verify all collected inputs with user before rule creation.

MANDATORY VERIFICATION STEP (Enhanced):

This tool MUST be called after all inputs are collected but before final rule completion. It presents a comprehensive summary of all collected inputs for user verification.

ENHANCED WITH AUTOMATIC RULE FINALIZATION: After user confirms verification, this tool can automatically finalize the rule by:

  1. Building complete I/O mapping based on task sequence and inputs

  2. Adding mandatory compliance outputs

  3. Setting rule status to ACTIVE

  4. Completing the rule creation process

HANDLES DUPLICATE INPUT NAMES WITH TASK ALIASES (Preserved):

  • Uses unique identifiers (TaskAlias.InputName) for each input

  • Properly maps each unique input to its specific task alias

  • Creates structured inputs for rule creation with unique names when needed

  • Maintains clear separation between inputs from different task instances

VERIFICATION REQUIREMENTS (Preserved):

  1. Show complete summary of ALL collected inputs with unique IDs

  2. Display both template files and parameter values

  3. Show file URLs for uploaded templates

  4. Present clear verification checklist

  5. Get explicit user confirmation

  6. Allow user to modify values if needed

  7. Prepare inputs for rule structure creation with proper task alias mapping

  8. NEW: Automatically finalize rule after user confirmation

VERIFICATION PRESENTATION FORMAT (Preserved): "INPUT VERIFICATION SUMMARY:

Please review all collected inputs before rule creation:

TEMPLATE INPUTS (Uploaded Files): ✓ Task Input: [TaskAlias.InputName] Task: [TaskAlias] ([TaskName]) → Input: [InputName] Format: [Format] File: [filename] URL: [file_url] Size: [file_size] bytes Status: ✓ Validated

PARAMETER INPUTS (Values): ✓ Task Input: [TaskAlias.InputName] Task: [TaskAlias] ([TaskName]) → Input: [InputName] Type: [DataType] Value: [user_value] Required: [Yes/No] Status: ✓ Set

VERIFICATION CHECKLIST: □ All required inputs collected □ Template files uploaded and validated □ Parameter values set and confirmed □ No missing or invalid inputs □ Ready for rule creation

Are all these inputs correct?

  • Type 'yes' to proceed with rule creation

  • Type 'modify [TaskAlias.InputName]' to change a specific input

  • Type 'cancel' to abort rule creation"

CRITICAL VERIFICATION RULES (Enhanced):

  • NEVER proceed to final rule creation without user verification

  • ALWAYS show complete input summary with unique identifiers

  • ALWAYS get explicit user confirmation

  • Allow input modifications using unique IDs

  • Validate completeness before approval

  • Prepare structured inputs for rule creation with proper task mapping

  • NEW: Automatically finalize rule with I/O mapping after confirmation

Args: collected_inputs: Dict containing all collected template files and parameter values with unique IDs

Returns: Dict containing verification status, user confirmation, and structured inputs for rule finalization

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collected_inputsYes

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; description carries full burden and excels by disclosing automatic rule finalization (I/O mapping, compliance outputs, ACTIVE status), duplicate input name handling via TaskAlias, and allowing mid-process modifications.

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?

Extremely long with extensive template/example text that could be summarized rather than quoted verbatim; however, content is front-loaded with critical requirements and structured with clear headers.

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 for a complex multi-step workflow tool; covers verification logic, finalization behavior, and return values despite existence of output schema, though sibling differentiation could explicitly mention contrast with confirm_parameter_input/confirm_template_input.

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?

Schema has 0% description coverage; description compensates by specifying collected_inputs contains 'template files and parameter values with unique IDs', though could further detail expected dictionary structure/keys.

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?

Clearly states it verifies collected inputs before rule creation, distinguishes from sibling collection tools (collect_parameter_input, collect_template_input) and creation tools (create_rule) by specifying it's a mandatory verification step with automatic finalization.

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 states 'MUST be called after all inputs are collected but before final rule completion' and 'NEVER proceed to final rule creation without user verification', providing clear temporal sequencing and alternatives (modify vs cancel).

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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