cadence

Capture lessons and write a persistent handoff plan at session end.

3|Updated Feb 18, 2026

Search Tags:#workflow automation #state management #session management #handoff #ai governance #knowledge persistence

Ready to run

npx skills add https://github.com/prompted365/context-grapple-gun --skill cadence

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cadence
Source: https://github.com/prompted365/context-grapple-gun/tree/main/cgg-runtime/skills/cadence
Command: npx skills add https://github.com/prompted365/context-grapple-gun --skill cadence

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the problem of knowledge loss at the end of AI sessions, ensuring that lessons learned and operational states are persistently captured and carried forward.

Core Features & Use Cases

Session Handoff: Creates a structured plan that bridges session states, ensuring continuity.
Knowledge Persistence: Captures lessons learned and operational decisions for future use.
Governance Lifecycle: Manages the AI's operational rules and promotes them through defined stages.
Use Case: At the end of a complex coding session, use /cadence to save all progress, document new insights, and prepare a clear set of next actions for the AI's next session, preventing loss of context and work.

Quick Start

Run the cadence skill to end the current session and save all progress.

Frequently Asked Questions about cadence

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

FAQPage Schema

How do I persist AI session state and prevent knowledge loss at the end of a workflow?▼

To persist AI session state and prevent knowledge loss, use a session lifecycle tool that captures lessons learned and writes a structured handoff plan. This ensures operational states and context are carried forward to the next session.

What is the best way to manage AI session handoffs for complex coding tasks?▼

The best way to manage AI session handoffs is to emit canonical state markers and generate a persistent handoff plan at session termination. This bridges operational states, documenting insights and defining clear next actions for continuity.

How does knowledge promotion work within AI governance lifecycle management?▼

Knowledge promotion within AI governance lifecycle management works by enforcing defined mechanisms that capture operational decisions and promote them through structured stages. This ensures rules and lessons persistently guide future AI sessions.

Can I use session management tools for emergency state persistence during unexpected interruptions?▼

Yes, you can use session management tools for emergency state persistence by triggering an emergency syncopate mode. This mode handles unexpected session termination by rapidly capturing operational states and writing a recovery handoff plan.

Do I need workflow automation dependencies to execute AI session lifecycle commands?▼

No, you do not need external workflow automation dependencies to execute AI session lifecycle commands. The skill operates independently using internal scripts and references to manage state, capture lessons, and write handoff plans.