context-compression

Name: context-compression
Availability: InStock
Author: ils15

Compress and prioritize project management context using scoring and summarization.

10|5|Updated Dec 12, 2025

Search Tags:#project management #context compression #cross-references #priority scoring #semantic summarization

Ready to run

npx skills add https://github.com/ils15/pantheon --skill context-compression-ils15

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: context-compression
Source: https://github.com/ils15/pantheon/tree/main/platform/windsurf/.windsurf/skills/context-compression
Command: npx skills add https://github.com/ils15/pantheon --skill context-compression-ils15

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill efficiently compresses context for streamlined workflow, enhancing productivity and maintaining critical information during transitions between phases.

Core Features & Use Cases

Priority Scoring Engine: Automatically scores context based on impact, risk, novelty, blockers, and downstream relevance.
Semantic Summarization: Generates summaries for critical and high-priority entries, tailored to downstream agents.
Downstream-Aware Compression: Applies field masks based on the relationship between agents.
Cross-Reference Mechanism: Automatically creates references for endpoints, tables, migrations, components, and decisions.

Quick Start

Use the context-compression skill to compress the current context for the next phase.

Frequently Asked Questions about context-compression

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

FAQPage Schema

How do I compress project management context to prevent information overload during phase transitions?▼

Context compression for project management works by scoring entries based on impact, risk, and downstream relevance, then generating semantic summaries for high-priority items. This mechanism automatically applies field masks to filter information specifically for downstream agents.

How does priority scoring work for context compression?▼

Priority scoring works by automatically evaluating context entries against impact, risk, novelty, blockers, and downstream relevance. This mechanism identifies critical project management details to ensure they are preserved during compression.

Can I use this context compression approach with Python scripting for data processing?▼

Yes, you can use this context compression approach with Python, as it requires Python for scripting and data processing. The scripts component handles the priority scoring and semantic summarization logic for your project management workflows.

What is the best way to maintain cross-references for endpoints and migrations when compressing context?▼

The best way to maintain cross-references when compressing context is using the automatic cross-reference mechanism. It identifies and creates references for endpoints, database tables, migrations, components, and decisions to preserve critical project relationships.

Does downstream-aware compression apply field masks based on agent relationships?▼

Yes, downstream-aware compression applies field masks based on the specific relationship between agents. This ensures that the compressed context only includes the relevant information required by the next downstream project management phase.