session-management

Load and persist .NET project context across AI engineering sessions.

224|87|Updated Dec 15, 2018
One-click install
npx skills add https://github.com/Resgrid/Core --skill session-management-resgrid
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: session-management
Source: https://github.com/Resgrid/Core/tree/main/.opencode/skills/session-management
Command: npx skills add https://github.com/Resgrid/Core --skill session-management-resgrid

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents wasted time and lost context by ensuring an AI session reliably loads prior handoff, rules, and project solution context, then captures new work before the session ends.

Core Features & Use Cases

  • Session start context loading: Loads .claude/handoff.md, MEMORY.md, and .claude/instincts.md, then detects the .NET solution (.slnx/.sln) to enable MCP tooling.
  • Session end capture & learning: Reviews accomplishments, checks git state, writes a new .claude/handoff.md, extracts learnings into MEMORY.md, and updates .claude/instincts.md.
  • Resumption without surprises: Summarizes pending work from an existing handoff and waits for user confirmation before continuing it.
  • Graceful degradation: Starts clean when context files or solution are missing and avoids blocking progress when MCP tools are unavailable.

Quick Start

Run session start when beginning a .NET work session, then end the session using the capture protocol so the next session can resume accurately.

Frequently Asked Questions about session-management

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

FAQPage Schema
How do I preserve AI context across sessions for .NET development?

You preserve AI context across sessions by loading handoff, memory, and instincts files at start, then writing updated context and extracted learnings back to those files at session end.

What is the best way to hand off an AI coding session without losing project state?

The best way to hand off an AI coding session is to review git state and accomplishments, then write a new handoff file with extracted learnings so the next session resumes accurately.

Does session management work with .NET solutions using .slnx or .sln files?

Yes, session management detects the appropriate .slnx or .sln file for your .NET solution to enable MCP tooling connectivity and ensure reliable context loading across sessions.

What happens to my AI session context if handoff or memory files are missing?

If handoff or memory files are missing, the session degrades gracefully by starting clean and avoiding blocked progress, while still detecting the .NET solution for MCP tooling.

Can I resume a previous AI engineering session and review pending work before continuing?

Yes, resuming an AI engineering session loads an existing handoff file, summarizes pending work from it, and waits for your confirmation before continuing any tasks.

How do I extract and save learnings from an AI coding session for future use?

You extract and save learnings by reviewing accomplishments at session end, writing updated handoff files, and persisting new insights into memory and instincts files for future context.