context-mode

Route large command outputs to ctx_execute or ctx_execute_file via PreToolUse.

3|1|Updated Aug 10, 2025
One-click install
npx skills add https://github.com/hckhanh/pulumi-any-terraform --skill context-mode-hckhanh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: context-mode
Source: https://github.com/hckhanh/pulumi-any-terraform/tree/main/.agents/skills/context-mode
Command: npx skills add https://github.com/hckhanh/pulumi-any-terraform --skill context-mode-hckhanh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Large command outputs and tool results can overwhelm the AI context, causing slowed responses or truncated analysis. Context-mode provides deterministic routing to specialized tools so the LLM only sees concise, relevant results.

Core Features & Use Cases

  • Automatic routing of large outputs to ctx_execute or ctx_execute_file to keep context lean.
  • Triggered for common tasks like "analyze logs", "summarize output", "parse JSON", "check build output", and other MCP results that exceed typical size limits.
  • Subagent routing is handled automatically via PreToolUse to ensure consistent behavior across tools and sessions.

Quick Start

Enable context-mode and let it automatically route large outputs to ctx_execute or ctx_execute_file for deterministic processing.

Frequently Asked Questions about context-mode

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

FAQPage Schema
How do I prevent large command outputs from flooding the LLM context?

Context-mode prevents large command outputs from flooding the LLM context by automatically routing oversized results to ctx_execute or ctx_execute_file. This deterministic routing ensures the LLM only processes concise, relevant summaries instead of raw data.

What is the best way to analyze large build logs without slowing down AI responses?

Analyzing large build logs without slowing down AI responses is best handled by context-mode. It intercepts logs exceeding 20 lines via PreToolUse subagent routing, processing them externally so the AI context remains lean and responsive.

When do I need context routing for MCP outputs and API responses?

You need context routing for MCP outputs and API responses when structured data exceeds typical size limits or 20 lines. Context-mode triggers automatically for tasks like parsing JSON or summarizing output, enforcing lean context management.

Does context-mode work automatically for log analysis tasks, or do I need manual configuration?

Context-mode works automatically for log analysis tasks without manual configuration. Once enabled, it enforces a default routing rule set and uses PreToolUse subagent routing to consistently manage large outputs across tools and sessions.

Can I use context routing to parse JSON and process large structured data from automation tasks?

Yes, you can use context routing to parse JSON and process large structured data from automation tasks. Context-mode targets common data processing tasks, automatically routing heavy outputs to ctx_execute_file for deterministic, context-safe extraction.