# Meta Context Budgeting > Techniques for managing the context window limit in long-running AI agents. Use when this capability is needed. - Skill: `tomevault-io/meta-context-budgeting` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/meta-context-budgeting` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/meta-context-budgeting/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/meta-context-budgeting --- # Meta-Context Budgeting AI models have a "budget" (the context window). Every token you use leaves less room for reasoning. ## Budgeting Strategies - **Purging**: Identifying and removing outdated logs, repetitive instructions, or completed task summaries once they are no longer needed. - **Summarization**: Compressing long technical discussions into concise action points before proceeding to the next phase. - **Priority Filtering**: Keeping "System Instructions" and "Foundational Constraints" at the highest priority, while ephemeral chat history is lower priority. ## Tools - **Token Counters**: Using tools to monitor current usage. - **Selective Retrieval**: Only fetching the most relevant "chunks" of a codebase or skill library. ## Best Practices - **Clean State**: Occasionally starting a fresh session and only carrying over the "Essential State" (ADRs, current plan, critical constraints). --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/jcorpac) — claim your Tome and manage your conversions.