# Openrouter Context Optimization

> Optimize token usage and context window management. Use when reducing costs or fitting more information into model context. Trigger with phrases like 'openrouter context', 'token optimization', 'context window', 'reduce tokens'.

- Skill: `micsapp/openrouter-context-optimization` (Agent Skill, multi-file: 10 files)
- Install (CLI): `npx skillmds@latest add micsapp/openrouter-context-optimization`
- Raw SKILL.md: https://api.skillmd.com/api/skills/micsapp/openrouter-context-optimization/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: micsapp (https://skillmd.com/u/micsapp)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/micsapp/openrouter-context-optimization

---

# Openrouter Context Optimization

## Overview

This skill covers techniques for managing token budgets, optimizing prompt length, and making the most of each model's context window.

## Prerequisites

- OpenRouter integration
- Tokenizer library (tiktoken for OpenAI models, or approximate counting)

## Instructions

1. **Count tokens before sending**: Use `tiktoken` (Python) or `js-tiktoken` (JS) to estimate token counts before making API calls; abort if the prompt exceeds the model's context limit
2. **Implement conversation pruning**: For multi-turn chats, drop or summarize older messages when total tokens approach the context limit, keeping system prompts and recent messages
3. **Optimize system prompts**: Move static instructions to the system message and keep them concise; every token in the system prompt is repeated on every request
4. **Use response length controls**: Set `max_tokens` to the minimum needed for your use case; shorter completions cost less and return faster
5. **Select models by context need**: Route short-context tasks to cheaper models and reserve large-context models (128K+) for tasks that genuinely need them

## Output

- Token budget calculator that warns before exceeding context limits
- Conversation pruning middleware that keeps chats within context bounds
- Cost reduction from optimized prompt engineering (typically 20-40% savings)

## Error Handling

| Error | Cause | Fix |
|-------|-------|-----|
| 400 `context_length_exceeded` | Prompt + max_tokens exceeds model limit | Prune messages or switch to a model with a larger context window |
| Truncated responses | `max_tokens` set too low | Increase `max_tokens` or split the task into smaller requests |
| Token count mismatch | Wrong tokenizer for the model | Use the correct tokenizer per model family; fall back to rough estimation (1 token ~ 4 chars) |

See `${CLAUDE_SKILL_DIR}/references/errors.md` for full error reference.

## Examples

See `${CLAUDE_SKILL_DIR}/references/examples.md` for runnable code samples.

## Resources

- [OpenRouter Documentation](https://openrouter.ai/docs)
- [OpenRouter Models](https://openrouter.ai/models)
- [OpenRouter API Reference](https://openrouter.ai/docs/api-reference)
- [OpenRouter Status](https://status.openrouter.ai)