petri-template-and-validation

Generate Petri nets from templates with static validation and fault-injection simulation.

3|Updated Mar 17, 2026

Search Tags:#template generation #llm-workflows #fault-injection #workflow migration #static validation #petri-net

Ready to run

npx skills add https://github.com/transreal/claudecode --skill petri-template-and-validation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: petri-template-and-validation
Source: https://github.com/transreal/claudecode/tree/main/Claude%20Directives/skills/petri-template-and-validation
Command: npx skills add https://github.com/transreal/claudecode --skill petri-template-and-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams stop recurring structural bugs in LLM-generated Petri nets by replacing free-form generation with template-based instantiation plus explicit validation and fault-simulation gates.

Core Features & Use Cases

Template-based Petri net generation: Generate net structure from vetted templates rather than letting the LLM free-write workflows.
Static validation as a formal transition: Detect unreachable/unproductive nodes, deadlocks, AND/XOR merge mismatches, and missing retry/trial-guard patterns before any execution.
Fault-injection simulation for behavioral safety: Run scenario-based dynamic checks without invoking additional LLM calls to confirm end states like Done vs Stuck.
Approval-gated execution planning: Route passing nets into runnable workflow instantiation with human or automatic approval.

Quick Start

Tell your team to implement proposePetriNet as a Petri-net self-hosting metaworkflow that selects a template, validates statically, simulates faults, and only then approves and instantiates the runnable net.

Frequently Asked Questions about petri-template-and-validation

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

FAQPage Schema

How do I prevent deadlocks in LLM-generated Petri nets?▼

Static validation acts as a formal transition gate to detect unreachable nodes, deadlocks, AND/XOR merge mismatches, and missing retry guards before any workflow execution begins.

How do I validate Petri net retry and merge semantics before execution?▼

You validate retry and merge semantics by running fault-injection simulation scenarios that dynamically check behavioral safety and confirm end states like Done versus Stuck without invoking additional LLM calls.

What is the best way to structure LLM workflow migration for production pipelines?▼

The best way to structure workflow migration is using a metaworkflow that parses intent, selects a vetted template, binds parameters, and enforces termination and deadlock avoidance before instantiating runnable nets.

Do I need approval gates for Petri net instantiation in production?▼

Yes, approval gates route statically validated and fault-simulated Petri nets into runnable workflow instantiation, ensuring human or automatic approval is required before production pipeline execution.

Can I use template-based generation instead of free-form LLM workflow creation?▼

Yes, template-based Petri net generation replaces free-form LLM output by selecting vetted templates and binding parameters, ensuring reliable structural and behavioral correctness under failure scenarios.