What problem does it solve?
This Skill helps prevent context overload and declining performance by teaching you how to manage limited model tokens during long coding and codebase exploration sessions.
Core Features & Use Cases
- MCP-first navigation: Prefer tool-based symbol lookup and API inspection over expensive file reads to minimize token consumption.
- Lazy loading: Read only what you need, when you need it, instead of preloading large swaths of the repository.
- Subagent isolation: Offload verbose exploration and analysis into subagents so summaries—not raw content—return to your main context.
- Summarize and discard: Convert explored information into compact summaries to keep your working context lean.
- Token budgeting: Plan read/analysis phases around an explicit token budget to avoid running out of context.
Quick Start
Load the context-discipline skill before starting a large codebase task, then use MCP tools to locate the relevant types and only read the specific files and methods you must change.