# Ck:context Engineering

> >-

- **Type:** Skill
- **Install:** `agentstack add skill-manhvann-codexkit-context-engineering`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [manhvann](https://agentstack.voostack.com/s/manhvann)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [manhvann](https://github.com/manhvann)
- **Source:** https://github.com/manhvann/codexkit/tree/main/.agents/skills/context-engineering

## Install

```sh
agentstack add skill-manhvann-codexkit-context-engineering
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Context Engineering

Context engineering curates the smallest high-signal token set for LLM tasks. The goal: maximize reasoning quality while minimizing token usage.

## When to Activate

- Designing/debugging agent systems
- Context limits constrain performance
- Optimizing cost/latency
- Building multi-agent coordination
- Implementing memory systems
- Evaluating agent performance
- Developing LLM-powered pipelines

## Core Principles

1. **Context quality > quantity** - High-signal tokens beat exhaustive content
2. **Attention is finite** - U-shaped curve favors beginning/end positions
3. **Progressive disclosure** - Load information just-in-time
4. **Isolation prevents degradation** - Partition work across sub-agents
5. **Measure before optimizing** - Know your baseline

**IMPORTANT:**
- Sacrifice grammar for the sake of concision.
- Ensure token efficiency while maintaining high quality.
- Pass these rules to subagents.

## Quick Reference

| Topic | When to Use | Reference |
|-------|-------------|-----------|
| **Fundamentals** | Understanding context anatomy, attention mechanics | [context-fundamentals.md](./references/context-fundamentals.md) |
| **Degradation** | Debugging failures, lost-in-middle, poisoning | [context-degradation.md](./references/context-degradation.md) |
| **Optimization** | Compaction, masking, caching, partitioning | [context-optimization.md](./references/context-optimization.md) |
| **Compression** | Long sessions, summarization strategies | [context-compression.md](./references/context-compression.md) |
| **Memory** | Cross-session persistence, knowledge graphs | [memory-systems.md](./references/memory-systems.md) |
| **Multi-Agent** | Coordination patterns, context isolation | [multi-agent-patterns.md](./references/multi-agent-patterns.md) |
| **Evaluation** | Testing agents, LLM-as-Judge, metrics | [evaluation.md](./references/evaluation.md) |
| **Tool Design** | Tool consolidation, description engineering | [tool-design.md](./references/tool-design.md) |
| **Pipelines** | Project development, batch processing | [project-development.md](./references/project-development.md) |
| **Runtime Awareness** | Usage limits, context window monitoring | [runtime-awareness.md](./references/runtime-awareness.md) |

## Key Metrics

- **Token utilization**: Warning at 70%, trigger optimization at 80%
- **Token variance**: Explains 80% of agent performance variance
- **Multi-agent cost**: ~15x single agent baseline
- **Compaction target**: 50-70% reduction, 
Codex Usage Limits: 5h=45%, 7d=32%
Context Window Usage: 67%

```

**Thresholds:**
- 70%: WARNING - consider optimization/compaction
- 90%: CRITICAL - immediate action needed

**Data Sources:**
- Usage limits: OpenAI OAuth API (`https://api.openai.com/api/oauth/usage`)
- Context window: Statusline temp file (`/tmp/ck-context-{session_id}.json`)

## Scripts

- [context_analyzer.py](./scripts/context_analyzer.py) - Context health analysis, degradation detection
- [compression_evaluator.py](./scripts/compression_evaluator.py) - Compression quality evaluation

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [manhvann](https://github.com/manhvann)
- **Source:** [manhvann/codexkit](https://github.com/manhvann/codexkit)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-manhvann-codexkit-context-engineering
- Seller: https://agentstack.voostack.com/s/manhvann
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.