func-spec

Extract DUT functional specifications into hierarchical YAML records via update_spec.py.

207|45|Updated May 27, 2025
One-click install
npx skills add https://github.com/XS-MLVP/UCAgent --skill func-spec
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: func-spec
Source: https://github.com/XS-MLVP/UCAgent/tree/main/ucagent/lang/zh/skills/formal/func-spec
Command: npx skills add https://github.com/XS-MLVP/UCAgent --skill func-spec

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill helps extract and organize DUT functional specifications and their formal detection points, converting scattered information into a reusable YAML structure for formal verification workflows.

Core Features & Use Cases

  • Develops a hierarchical FG/FC/CK model to capture environment constraints, functional points, and checks.
  • Automates updates to .formal_records.yaml via the update_spec.py script, ensuring consistent structure.
  • Guides users from RTL/document inputs to formal verification planning with safe, script-driven edits.

Quick Start

Run the update_spec.py script to add FG/FC/CK entries for your DUT and generate the formal specification document.

Frequently Asked Questions about func-spec

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

FAQPage Schema
How do I extract DUT functional specifications for formal verification?

Extracting DUT functional specifications for formal verification involves organizing RTL inputs and detection points into a structured YAML format using a script-driven FG/FC/CK hierarchy to capture environment constraints and checks.

What is the FG/FC/CK hierarchy in formal verification planning?

The FG/FC/CK hierarchy in formal verification planning is a structured model that captures environment constraints, functional points, and formal checks to systematically derive functional coverage plans from DUT specifications.

How do I update .formal_records.yaml with new functional checks?

Updating .formal_records.yaml with new functional checks requires running the update_spec.py script, which validates the YAML structure and safely adds hierarchical FG/FC/CK entries for your DUT.

Can I derive formal checks directly from RTL design documents?

Deriving formal checks directly from RTL design documents is supported by extracting functional specifications into a reusable YAML structure, enabling automated formal detection point generation for verification workflows.

Does update_spec.py validate the YAML structure for DUT formal specifications?

Yes, update_spec.py validates the YAML structure for DUT formal specifications while enforcing the FG/FC/CK hierarchy, ensuring consistent organization of environment constraints, functional points, and formal detection checks.

What are the limitations of using a script-driven approach for formal coverage planning?

Limitations of script-driven formal coverage planning include strict dependency on YAML structure validation and the FG/FC/CK hierarchy, meaning invalid inputs or deviations from the update_spec.py workflow will fail to generate the formal specification document.