context-compactor
Token-based context compaction for local models (MLX, llama.cpp, Ollama) that don't report context limits.
Best use case
context-compactor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Token-based context compaction for local models (MLX, llama.cpp, Ollama) that don't report context limits.
Teams using context-compactor 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-compactor/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How context-compactor Compares
| Feature / Agent | context-compactor | 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?
Token-based context compaction for local models (MLX, llama.cpp, Ollama) that don't report context limits.
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-compactor Token-based context compaction for local models (MLX, llama.cpp, Ollama) that don't report context limits. ## Install ``` npx clawhub@latest install context-compactor ```
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