resuming-context

Restore working context from session-summary.md and delegate to the next skill.

1|Updated Apr 12, 2026
One-click install
npx skills add https://github.com/fascari/ai-config --skill resuming-context
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: resuming-context
Source: https://github.com/fascari/ai-config/tree/main/skills/resuming-context
Command: npx skills add https://github.com/fascari/ai-config --skill resuming-context

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates restoring a full working context from a compressed session and resumes the correct skill flow so work continues where it was interrupted.

Core Features & Use Cases

  • Rehydrates context by reading session-summary.md, progress.md, and implementation-plan.md and routing to the appropriate skill.
  • Restores key decisions from the session and enforces them as constraints for subsequent steps.
  • Determines the exact resume point by cross-referencing session sections with progress state and resumes from the correct sub-task.
  • Presents a restoration summary to the user before delegating to the next skill.
  • Delegates to the appropriate skill (e.g., researching-codebase, planning-implementation, implementing-feature, reviewing-code, or committing-changes) based on the resume point.

Quick Start

Paste a compressed session-summary.md to restore context and continue the session.

Frequently Asked Questions about resuming-context

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

FAQPage Schema
How do I resume an interrupted AI workflow session?

To resume an interrupted AI workflow session, paste a compressed session-summary.md to rehydrate the context and seamlessly hand off to the appropriate skill. The system reads session files, restores key decisions as constraints, and determines the exact resume point.

What is context rehydration for multi-step AI-assisted workflows?

Context rehydration is the process of reconstructing a complete working context from a compressed session. It restores key decisions as hard constraints and cross-references progress state to seamlessly resume multi-step AI-assisted workflows from the correct sub-task.

How do I restore key decisions as hard constraints when continuing a workflow?

Restoring key decisions as hard constraints happens automatically when you paste a session-summary.md. The system reads the session files, extracts previous decisions, and enforces them as constraints for subsequent steps before delegating to the next skill.

Can I continue a multi-step workflow across planning, implementation, and review?

Yes, you can continue a multi-step workflow across planning, implementation, testing, and review. The system determines the exact resume point by cross-referencing session sections with progress state and delegates to the appropriate skill like planning-implementation or reviewing-code.

What's the best way to manage session state for AI-assisted coding tasks?

The best way to manage session state for AI-assisted coding tasks is using session-summary.md, progress.md, and implementation-plan.md files. The system reads these files to reconstruct context, identify the last completed task, and route to the appropriate skill to continue.

Do I need a session-summary.md to restore context and continue working?

Yes, you need a compressed session-summary.md to restore context and continue working. The system uses this file alongside progress.md and implementation-plan.md to reconstruct the complete working context and determine the exact resume point before handing off.