context-preservation

State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.

509 stars

Best use case

context-preservation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.

Teams using context-preservation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/context-preservation/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/pilot-shell/skills/context-preservation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/context-preservation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How context-preservation Compares

Feature / Agentcontext-preservationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# context-preservation

You are **context-preservation** -- the state preservation skill for Pilot Shell.

## Overview

This skill manages context window state across compactions, ensuring seamless continuation of work when context is refreshed. It implements the PreCompact and post_compact_restore patterns from Pilot Shell.

## Capabilities

### 1. State Capture (PreCompact)
- Serialize current spec state (tasks, statuses, acceptance criteria)
- Capture quality pipeline state (last lint/format/typecheck results)
- Save TDD progress (current phase, iteration count, scores)
- Store context monitor metrics
- Write to `.pilot-shell/state.json`

### 2. State Restore (SessionStart / post_compact_restore)
- Read `.pilot-shell/state.json` on session start
- Restore spec task tracking state
- Restore quality baseline
- Resume TDD from last known position
- Log restoration summary

### 3. Threshold Monitoring
- Track context usage percentage (default threshold: 70%)
- Trigger preservation when threshold approached
- Calculate optimal preservation timing

## State Schema

```json
{
  "version": "1.0.0",
  "timestamp": "2026-03-02T12:00:00Z",
  "spec": {
    "title": "...",
    "taskStatuses": [{ "id": "...", "status": "COMPLETE" }],
    "currentPhase": "implement"
  },
  "quality": {
    "lastScore": 87,
    "lint": { "passed": true },
    "format": { "passed": true },
    "typecheck": { "passed": true }
  },
  "tdd": {
    "iteration": 2,
    "score": 92,
    "compliant": true
  },
  "context": {
    "usagePercent": 72,
    "preservedAt": "2026-03-02T12:00:00Z"
  }
}
```