context-optimizer
The context-optimizer Claude Code skill provides diagnostic commands and strategies for managing token consumption and context window degradation during extended Claude sessions. Use it when session performance declines, context utilization exceeds 70 percent, or remaining token budget becomes constrained, implementing techniques like selective compaction, MCP auditing, subagent delegation, and prompt engineering to maintain efficiency across planning, implementation, testing, and review phases.
git clone --depth 1 https://github.com/rohitg00/pro-workflow /tmp/context-optimizer && cp -r /tmp/context-optimizer/skills/context-optimizer ~/.claude/skills/context-optimizerSKILL.md
# Context Optimizer
Manage your context window and token budget effectively.
## Quick Diagnosis
1. Run `/context` to check current usage
2. If > 70% → compact now before it degrades
3. If > 90% → you're in the "dumb zone", compact immediately
## Optimization Strategies
### Immediate
| Action | Saves | When |
|--------|-------|------|
| `/compact` | 30-50% context | At task boundaries |
| Disable unused MCPs | ~5% per MCP | When switching domains |
| Use subagents for exploration | Keeps main context clean | Heavy search/read tasks |
| Fresh session via `/resume` | 100% reset | When starting unrelated work |
### Configuration
Set proactive auto-compaction:
```json
{
"env": {
"CLAUDE_AUTOCOMPACT_PCT_OVERRIDE": "50"
}
}
```
### MCP Audit
Keep <10 MCPs enabled, <80 tools total. Each MCP adds overhead to every request.
```bash
/mcp # List active servers
# Disable what you're not using
```
### Prompt Engineering for Token Efficiency
- Scope your prompts: "In src/auth/, fix the login bug"
- Provide constraints: "Don't modify the middleware"
- Give acceptance criteria: "Should return 429 after 5 attempts"
- Avoid vague prompts: "Fix the code" (forces Claude to read everything)
### Subagent Delegation
Heavy operations that generate lots of output should go to subagents:
- Test suite output → subagent
- Large file exploration → subagent
- Documentation generation → subagent
- Log analysis → subagent
The main session stays clean while subagents handle the volume.
## Context Budget Planning
| Phase | Target Usage | Action If Over |
|-------|-------------|----------------|
| Planning | < 20% | Keep plans concise |
| Implementation | < 60% | Compact between files |
| Testing | < 80% | Delegate to subagent |
| Review | < 90% | Start fresh session |
## Token Efficiency
### Output Reduction (40-60% savings)
- No sycophantic openers ("Sure!", "Great question!")
- No closing fluff ("Let me know if you need anything!")
- No prompt restatement before answering
- Code first, explanation only if non-obvious
- Structured output (tables, bullets) over prose
- ASCII only: -- not em dashes, straight quotes not smart quotes
### Behavioral Efficiency
- One-pass coding: complete solution, test once, stop if green
- Read before write: never modify unread files
- No re-reads: don't re-read unchanged files
- Tool-call budgets: 20 (quick fix) to 80 (large feature)
- Never iterate more than twice on the same failure
### Task Profiles
Switch response style based on context:
- **Coding**: code first, minimal explanation, simplest solution
- **Agent/Pipeline**: structured output only, no prose, parseable
- **Analysis**: finding first, tables over paragraphs, sourced numbers
## CLAUDE.md Optimization
- Root CLAUDE.md: < 60 lines ideal, < 150 max
- Move package-specific info to package-level CLAUDE.md
- Move personal preferences to CLAUDE.local.md
- Remove obvious or rapidly-changing information
## When Context Is Degraded
Signs:
- Claude repeats itself or forgets earlier context
- Responses become generic or lose project-specific knowledge
- Tool calls start failing for reasons that worked earlier
Fix:
1. Manual `/compact`
2. If still bad: new session with `/resume`
3. For recurring issues: reduce CLAUDE.md size, disable MCPsCoordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
Analyzes and optimizes context window usage across sessions. Use when context feels bloated, sessions run slow, or approaching compaction limits.
Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
Analyze session token usage and cost patterns. Identify expensive operations and recommend optimizations. Use to understand and reduce session costs.