---
name: strategic-compact-3ab1bf4cd058
description: Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
origin: ecc
---

# 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 `~/.codex/settings.json`:

```json
{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Edit",
        "hooks": [{ "type": "command", "command": "node ~/.codex/scripts/hooks/suggest-compact.js" }]
      },
      {
        "matcher": "Write",
        "hooks": [{ "type": "command", "command": "node ~/.codex/scripts/hooks/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 |
|----------|------|
| CODEX.md instructions | Intermediate reasoning and analysis |
| TodoWrite task list | File contents you previously read |
| Memory files (`~/.codex/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`

## Token Optimization Patterns

### Trigger-Table Lazy Loading
Instead of loading full skill content at session start, use a trigger table that maps keywords to skill paths. Skills load only when triggered, reducing baseline context by 50%+:

| Trigger | Skill | Load When |
|---------|-------|-----------|
| "test", "tdd", "coverage" | tdd-workflow | User mentions testing |
| "security", "auth", "xss" | security-review | Security-related work |
| "deploy", "ci/cd" | deployment-patterns | Deployment context |

### Context Composition Awareness
Monitor what's consuming your context window:
- **CODEX.md files** — Always loaded, keep lean
- **Loaded skills** — Each skill adds 1-5K tokens
- **Conversation history** — Grows with each exchange
- **Tool results** — File reads, search results add bulk

### Duplicate Instruction Detection
Common sources of duplicate context:
- Same rules in both `~/.codex/rules/` and project `.codex/rules/`
- Skills that repeat CODEX.md instructions
- Multiple skills covering overlapping domains

### Context Optimization Tools
- `token-optimizer` MCP — Automated 95%+ token reduction via content deduplication
- `context-mode` — Context virtualization (315KB to 5.4KB demonstrated)

## Related

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


---
Source attribution: mturac
Original project: https://github.com/mturac/everything-openai-codex/blob/b5057da5f42ed6b12cd3a59e89af0ccd12cff7c2/skills/strategic-compact/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Mehmet Turac

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


## Additional upstream notices

strategic-compact-3ab1bf4cd058/DAVEAI-UPSTREAM-NOTICE.md

# Notices and Acknowledgements

Everything OpenAI Codex is a Codex-focused adaptation inspired by the public
[`affaan-m/everything-claude-code`](https://github.com/affaan-m/everything-claude-code)
project.

Respect to Affaan Mustafa and the contributors to that project for making the
multi-harness agent operating-system pattern visible in the open.

This repository adapts the public idea and workflow surface for OpenAI Codex:
names, defaults, install targets, docs, validators, and cross-harness guidance
are maintained here for the Codex-oriented project.


# Mega AI Hub resource metadata

Creator / publisher: mturac
Original project: https://github.com/mturac/everything-openai-codex/blob/b5057da5f42ed6b12cd3a59e89af0ccd12cff7c2/skills/strategic-compact/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Marketing, Product Management
Roles: Data Analyst, Growth Marketer, Product Manager
Specialties: API
Tools: Codex
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 52b3faf9a8fa7b82679ee08b7804f5267a3777ddb21451145a22830a49a3a2a0