strategic-compact

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

144,923 stars
Complexity: easy

About this skill

The Strategic Compact skill empowers AI agents, particularly Claude, to intelligently manage their conversational context. Instead of relying on potentially disruptive automatic context compaction, this skill instructs the agent to suggest manual `/compact` operations at strategic, human-defined intervals. This approach ensures critical information is preserved across distinct task phases (e.g., research, planning, implementation, testing), preventing the loss of important details that can occur when auto-compaction triggers mid-task. By enabling the agent to recommend compaction at natural breakpoints, it optimizes context coherence, improves response quality, and mitigates the risk of reaching token limits in long or complex sessions. This skill is a core component of the 'everything-claude-code' repository, emphasizing best practices for robust AI agent interaction.

Best use case

To maintain comprehensive context and coherence for AI agents during extended, multi-phase, or complex tasks, especially when approaching token limits or transitioning between distinct topics.

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

Improved coherence and quality of agent responses over long interactions. Prevention of critical context loss between task phases. More efficient use of the context window, helping to avoid token limit issues. Reduced instances of the AI agent 'drifting' or 'forgetting' previously discussed important details.

Practical example

Example input

Alright, I've finished reviewing the API design for the user authentication module. Now, let's start writing the actual implementation code for the `login` endpoint, focusing on security best practices.

Example output

It sounds like we're transitioning to a new major phase of the project. To ensure we maintain optimal context coherence for the implementation phase and prevent any loss of detail from our extensive design discussions, I recommend a manual context compaction now. Would you like me to `/compact` our session?

When to use this skill

  • Running long sessions that approach context limits (e.5., 200K+ tokens)
  • Working on multi-phase tasks (e.g., research → plan → implement → test)
  • Switching between unrelated tasks within the same session
  • After completing a major milestone and starting new work

When not to use this skill

  • Short, simple, or single-turn conversations where context management is not critical.
  • Tasks where the entire conversation is short and fits well within the context window.
  • When the agent's platform handles auto-compaction flawlessly for the specific task at hand and manual intervention offers no benefit.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/strategic-compact/SKILL.md --create-dirs "https://raw.githubusercontent.com/affaan-m/everything-claude-code/main/.agents/skills/strategic-compact/SKILL.md"

Manual Installation

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

How strategic-compact Compares

Feature / Agentstrategic-compactStandard Approach
Platform SupportClaudeLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

Which AI agents support this skill?

This skill is designed for Claude.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

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.

Related Guides

SKILL.md Source

# Strategic Compact Skill

Suggests manual `/compact` at strategic points in your workflow rather than relying on arbitrary auto-compaction.

## When to Activate

- Running long sessions that approach context limits (200K+ tokens)
- Working on multi-phase tasks (research → plan → implement → test)
- Switching between unrelated tasks within the same session
- After completing a major milestone and starting new work
- When responses slow down or become less coherent (context pressure)

## Why Strategic Compaction?

Auto-compaction triggers at arbitrary points:
- Often mid-task, losing important context
- No awareness of logical task boundaries
- Can interrupt complex multi-step operations

Strategic compaction at logical boundaries:
- **After exploration, before execution** — Compact research context, keep implementation plan
- **After completing a milestone** — Fresh start for next phase
- **Before major context shifts** — Clear exploration context before different task

## How It Works

The `suggest-compact.js` script runs on PreToolUse (Edit/Write) and:

1. **Tracks tool calls** — Counts tool invocations in session
2. **Threshold detection** — Suggests at configurable threshold (default: 50 calls)
3. **Periodic reminders** — Reminds every 25 calls after threshold

## Hook Setup

Add to your `~/.claude/settings.json`:

```json
{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Edit",
        "hooks": [{ "type": "command", "command": "node ~/.claude/skills/strategic-compact/suggest-compact.js" }]
      },
      {
        "matcher": "Write",
        "hooks": [{ "type": "command", "command": "node ~/.claude/skills/strategic-compact/suggest-compact.js" }]
      }
    ]
  }
}
```

## Configuration

Environment variables:
- `COMPACT_THRESHOLD` — Tool calls before first suggestion (default: 50)

## Compaction Decision Guide

Use this table to decide when to compact:

| Phase Transition | Compact? | Why |
|-----------------|----------|-----|
| Research → Planning | Yes | Research context is bulky; plan is the distilled output |
| Planning → Implementation | Yes | Plan is in TodoWrite or a file; free up context for code |
| Implementation → Testing | Maybe | Keep if tests reference recent code; compact if switching focus |
| Debugging → Next feature | Yes | Debug traces pollute context for unrelated work |
| Mid-implementation | No | Losing variable names, file paths, and partial state is costly |
| After a failed approach | Yes | Clear the dead-end reasoning before trying a new approach |

## What Survives Compaction

Understanding what persists helps you compact with confidence:

| Persists | Lost |
|----------|------|
| CLAUDE.md instructions | Intermediate reasoning and analysis |
| TodoWrite task list | File contents you previously read |
| Memory files (`~/.claude/memory/`) | Multi-step conversation context |
| Git state (commits, branches) | Tool call history and counts |
| Files on disk | Nuanced user preferences stated verbally |

## Best Practices

1. **Compact after planning** — Once plan is finalized in TodoWrite, compact to start fresh
2. **Compact after debugging** — Clear error-resolution context before continuing
3. **Don't compact mid-implementation** — Preserve context for related changes
4. **Read the suggestion** — The hook tells you *when*, you decide *if*
5. **Write before compacting** — Save important context to files or memory before compacting
6. **Use `/compact` with a summary** — Add a custom message: `/compact Focus on implementing auth middleware next`

## Related

- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) — Token optimization section
- Memory persistence hooks — For state that survives compaction
- `continuous-learning` skill — Extracts patterns before session ends

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