session-bridge

Save coding-session context to append-only .topia files for resume.

1|Updated May 18, 2026
One-click install
npx skills add https://github.com/linenoize/topia --skill session-bridge-linenoize
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: session-bridge
Source: https://github.com/linenoize/topia/tree/main/skills/session-bridge
Command: npx skills add https://github.com/linenoize/topia --skill session-bridge-linenoize

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Session-bridge prevents context loss between AI coding sessions by saving decisions, conventions, progress, and resume state into project-local .topia files so work can continue cleanly after compaction, restarts, or handoffs.

Core Features & Use Cases

  • Cross-session persistence: Captures architectural decisions, established patterns, task progress, session logs, and cumulative project notes.
  • Reliable resume support: Restores the next session with checkpoints, remaining tasks, and load-bearing context so the agent can pick up exactly where it left off.
  • Autonomous orchestration: Manages integrity checks, invariant loading, typed learning logs, and filesystem-based detach and reattach flows for slower second-opinion dispatches.
  • Use case: A team finishes a refactor, saves the current checkpoint, and later resumes with the same conventions, open questions, and next steps already loaded.

Quick Start

Ask session-bridge to save the current repository state so the next session can resume with the latest decisions, conventions, progress, and checkpoint information.

Frequently Asked Questions about session-bridge

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

FAQPage Schema
How do I preserve coding agent context across sessions?

Preserving coding agent context across sessions involves saving decisions, conventions, and progress into project-local files. This approach prevents context loss between AI agent runs, allowing work to continue cleanly after compaction, restarts, or handoffs.

What is the best way to restore checkpoint and task progress for an AI coding agent?

Restoring checkpoint and task progress requires loading saved state from project-local files. This technique restores the next session with remaining tasks and load-bearing context so the agent picks up exactly where it left off.

How does filesystem coordination work for autonomous workflow orchestration?

Filesystem coordination for autonomous workflow orchestration works by using append-only state management and idempotent operations. This ensures reliable resume and reattach behavior for slower second-opinion dispatches and autonomous sessions.

Can I use session checkpointing for team handoffs and autonomous agent sessions?

Yes, session checkpointing supports both team handoffs and autonomous agent sessions. It manages integrity checks, invariant loading, and detach protocol state across local repositories, ensuring reliable resume behavior for collaborative or autonomous work.

Do I need append-only state management for reliable context recovery?

Yes, append-only state management is required for reliable context recovery. It ensures integrity verification and invariant loading are maintained, preventing data corruption during checkpoint generation and filesystem coordination.

Why does context disappear between AI agent runs after a session restart?

Context disappears between AI agent runs because session memory is not natively preserved after restarts or compaction. Saving decisions and resume state into project-local files prevents this loss and enables reliable workflow orchestration.