context-pruner

Prune context irrelevant to the active objective within a goal-oriented harness.

Updated May 11, 2026

Search Tags:#token-optimization #context-management #harness #ai-workflow #cost-efficiency

Ready to run

npx skills add https://github.com/AesopScott/mojo --skill context-pruner

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: context-pruner
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/context-pruner
Command: npx skills add https://github.com/AesopScott/mojo --skill context-pruner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses excessive token consumption and compute waste by identifying and removing context that is not relevant to the active objective.

Core Features & Use Cases

Context Boundary Control: Dynamically prunes irrelevant data to maintain focus on the current goal.
Cost Efficiency: Reduces token spend and processing overhead by filtering out noise before model execution.
Use Case: When working on a complex project with a large history, use this skill to strip away outdated logs and irrelevant conversation threads to ensure the model focuses only on the current task.

Quick Start

Invoke the context-pruner skill to analyze the current goal and remove all context that does not directly support the active objective.

Frequently Asked Questions about context-pruner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I reduce token consumption when working with large project histories?▼

Reduce token consumption by pruning irrelevant context. This Skill identifies and removes outdated logs and irrelevant conversation threads, ensuring the model focuses only on the active objective to cut compute waste.

What is context boundary control and when do I need it for AI workflows?▼

Context boundary control dynamically prunes irrelevant data to maintain focus on the current goal. You need it in complex development workflows requiring strict boundary control over token usage and compute resources.

How do I prune irrelevant context to maintain focus on a current task?▼

Prune irrelevant context by invoking this Skill to analyze the current goal and remove all data that does not directly support the active objective within your specific harness boundary.

Do I need to define a specific harness boundary before pruning context?▼

Yes, you need to define a specific harness boundary. Safe and effective pruning requires a clear definition of both the current objective and the harness boundary to prevent removing relevant data.

What is the best way to optimize token efficiency in complex development workflows?▼

Optimize token efficiency by filtering out noise before model execution. This approach strips away irrelevant context, reducing token spend and processing overhead while maintaining active goal focus.

When should I not use automated context pruning for my AI model?▼

Avoid automated context pruning when you cannot clearly define the active objective or the specific harness boundary. Without these definitions, pruning risks removing relevant data needed for safe execution.