strategic-compact
For AI engineering, this skill suggests manual context compression at logical key points to optimize model performance and resource utilization, ensuring efficient AI system operation.
npx skills add https://github.com/affaan-m/everything-claude-code --skill strategic-compactBefore / After Comparison
1 组In long conversations or complex tasks, context is easily lost, leading to misunderstandings by the AI. This requires frequent manual adjustments, impacting interaction fluency and overall efficiency.
Intelligent suggestions perform context compression at logical intervals, effectively maintaining conversational coherence. This ensures the AI consistently understands the core intent, significantly improving interaction quality and task completion efficiency.
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:
- Tracks tool calls — Counts tool invocations in session
- Threshold detection — Suggests at configurable threshold (default: 50 calls)
- Periodic reminders — Reminds every 25 calls after threshold
Hook Setup
Add to your ~/.claude/settings.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
- Compact after planning — Once plan is finalized in TodoWrite, compact to start fresh
- Compact after debugging — Clear error-resolution context before continuing
- Don't compact mid-implementation — Preserve context for related changes
- Read the suggestion — The hook tells you when, you decide if
- Write before compacting — Save important context to files or memory before compacting
- Use
/compactwith 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:
- CLAUDE.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
~/.claude/rules/and project.claude/rules/ - Skills that repeat CLAUDE.md instructions
- Multiple skills covering overlapping domains
Context Optimization Tools
token-optimizerMCP — Automated 95%+ token reduction via content deduplicationcontext-mode— Context virtualization (315KB to 5.4KB demonstrated)
Related
- The Longform Guide — Token optimization section
- Memory persistence hooks — For state that survives compaction
continuous-learningskill — Extracts patterns before session ends
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