compliance-judgment

Evaluate extracted entities against verification rules and return structured judgments.

13|4|Updated Apr 27, 2026
One-click install
npx skills add https://github.com/memect/kc --skill compliance-judgment
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compliance-judgment
Source: https://github.com/memect/kc/tree/main/template/skills/zh/compliance-judgment
Command: npx skills add https://github.com/memect/kc --skill compliance-judgment

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Determine whether extracted entities comply with verification rules and translate rule intent into actionable judgments, enabling transparent, auditable verification.

Core Features & Use Cases

  • Converts natural-language verification rules into executable logic for deterministic or LLM-assisted judgments.
  • Applies per-document, per-rule evaluation to identify pass/fail conditions and produce actionable comments for failures.
  • Useful for designing, debugging, or auditing the judgment step of a compliance workflow.

Quick Start

Feed extracted entities and verification rules to produce per-document pass/fail judgments for each rule.

Frequently Asked Questions about compliance-judgment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify if extracted entities comply with specific compliance rules?

To verify extracted entities comply with compliance rules, this skill evaluates each document-rule pair using deterministic Python calculations for exact checks and worker LLMs for semantic judgments. It returns structured pass/fail results with actionable comments and confidence scores.

What is the best way to automate compliance judgment for multiple documents?

The best way to automate compliance judgment across multiple documents is applying per-document, per-rule evaluation logic. This approach converts natural-language verification rules into executable logic, producing transparent and auditable pass/fail judgments for each extracted entity.

Can I use LLMs for semantic compliance checks instead of deterministic rules?

Yes, you can use LLMs for semantic compliance checks. This skill specifically chooses worker LLMs for semantic evaluation when deterministic logic is insufficient, while applying Python calculations for standard deterministic verification tasks.

Does the compliance judgment workflow return structured JSON data?

Yes, the compliance judgment workflow returns a JSON-ready structure. Each evaluation result includes specific fields like field_id, document, result, extracted_value, expected, comment, and confidence for seamless downstream integration.

How do I debug failed compliance verification rules in my extraction workflow?

To debug failed compliance verification rules, feed your extracted entities and verification rules to this skill. It identifies specific pass/fail conditions and produces actionable comments explaining failures, enabling transparent and auditable verification debugging.