context-optimizer
Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
Best use case
context-optimizer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
Teams using context-optimizer 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/context-optimizer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How context-optimizer Compares
| Feature / Agent | context-optimizer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
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 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 |
## 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 MCPsRelated Skills
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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.
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