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ComplianceCow

ComplianceCow MCP Server

get_tasks_summary

Retrieve minimal task summaries for compliance workflows, analyze output intentions, and automatically suggest additional tasks to ensure complete and actionable deliverables.

Instructions

Resource containing minimal task information for initial selection.

This tool is also used as a fallback resource when fetch_tasks_suggestions is disabled or does not return suitable matches, ensuring the user always has access to a broader list of available tasks for manual selection.

This resource provides only the essential information needed for task selection:

  • Task name and display name

  • Brief description

  • Purpose and capabilities

  • Tags for categorization

  • Inputs/Outputs params with minimal details

  • Basic README summary

Use this for initial task discovery and selection. Detailed information can be retrieved later using tasks://details/{task_name} for selected tasks only.

AUTOMATIC OUTPUT ANALYSIS BY INTENTION:

  • MANDATORY: Analyze each task's output purpose and completion level during selection

  • IDENTIFY output intentions that require follow-up processing:

    • SPLITTING INTENTION: Outputs that divide data into separate categories → REQUIRE consolidation

    • EXTRACTION INTENTION: Outputs that pull raw data without formatting → REQUIRE transformation

    • VALIDATION INTENTION: Outputs that check compliance without final reporting → REQUIRE analysis/reporting

    • PROCESSING INTENTION: Outputs that transform data but don't create final deliverables → REQUIRE finalization

OUTPUT COMPLETION ASSESSMENT:

  • EVALUATE: Does this output serve as a final deliverable for end users?

  • ASSESS: Is this output consumable without additional processing?

  • DETERMINE: Does this output require combination with other outputs to be meaningful?

  • IDENTIFY: Is this output an intermediate step in a larger workflow?

WORKFLOW COMPLETION ENFORCEMENT:

  • NEVER present task selections that end with intermediate processing outputs

  • AUTOMATICALLY suggest tasks that fulfill incomplete intentions

  • ENSURE every workflow produces actionable final deliverables

  • RECOMMEND tasks that bridge gaps between current outputs and user goals

Mandatory functionality:

  • Retrieve a list of task summaries based on the user's request

  • Analyze task outputs and suggest additional tasks for workflow completion

  • If no matching task is found for the requested functionality, prompt user for confirmation

  • Based on user response, either proceed accordingly or create support ticket using create_support_ticket()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations exist, so the description must carry the burden. It covers basic return content but omits details like pagination or idempotency. The heavy mix of agent instructions confuses the tool's own behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very long and includes entire sections of agent instructions (analysis, enforcement, etc.) that are not about the tool. It lacks conciseness and mixes concerns.

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?

Given zero parameters and an output schema, the description covers the basic context (what it returns and when to use). However, the extraneous instructions detract from completeness and clarity.

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?

Input schema has zero parameters and 100% coverage. The description adds nothing extra about parameters, but none are needed. Baseline 4 is appropriate.

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?

The description states it provides minimal task information for initial selection and is a fallback when fetch_tasks_suggestions fails. The core purpose is clear, but it also includes extensive instructions that go beyond the tool's role.

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 says when to use it (initial discovery, fallback) and mentions an alternative (tasks://details/ for details). Good guidance on context.

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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