context-loading
Load minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.
git clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-skills /tmp/context-loading && cp -r /tmp/context-loading/skills/context-loading ~/.claude/skills/context-loadingSKILL.md
## Overview More context is not better context. Irrelevant context dilutes attention, increases cost, and slows inference. This skill enforces disciplined context loading: only the files, docs, and history that the current task requires. ## When to Use - Before starting any complex agent task - When designing system prompts for production agents - When context windows are filling up ## Process ### Step 1: Identify Required Context 1. List the files/docs the agent needs to read to complete THIS specific task. 2. For each item, ask: *"Can the agent complete the task without this?"* If yes, don't include it. 3. Prioritize: system prompt → task definition → directly relevant code → supporting references. **Verify:** Every item in context is directly necessary for the current task. ### Step 2: Summarize, Don't Dump 4. Long conversation history → summarize to key decisions and current state. 5. Large files → extract only the relevant functions/sections. 6. Entire docs → extract only the relevant sections. 7. Previous agent output → extract only the conclusions and next steps. **Verify:** No item in context exceeds what's needed from that source. ### Step 3: Set Context Budgets 8. Define token allocation for each context section: - System prompt: ≤ 2,000 tokens - Task definition: ≤ 500 tokens - Code context: ≤ 4,000 tokens - Conversation history (summarized): ≤ 1,000 tokens 9. Stay well within model context limits (leave 30% buffer for output). **Verify:** Total prompt fits within 70% of model context limit. ### Step 4: Refresh Context for New Tasks 10. Don't carry over context from a completed task to a new task. 11. Start each distinct task with a fresh, minimal context. 12. Re-introduce only what the new task genuinely needs. ## Verification - [ ] Context items limited to task-required items only - [ ] Long content summarized before inclusion - [ ] Token budget defined and respected - [ ] Context window at ≤70% capacity ## References - [rag-and-memory skill](../rag-and-memory/SKILL.md) - [multi-agent-orchestration skill](../multi-agent-orchestration/SKILL.md)
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Automated quality gates from commit to production. Every merge to main is potentially shippable. No manual steps in the deployment path.
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