context-engineering

## Overview Context is finite. What you put in the context window determines what the agent can reason about. Too much noise → the relevant signal is diluted. Too little context → the agent makes uninformed decisions. This skill manages context deliberately. ## When to Use - When an agent produces low-quality outputs despite correct instructions - When designing a system prompt for a production agent - When a long conversation is causing quality degradation - When context costs are higher than expected ## Process ### Step 1: Define the context budget For your model and use case: how many tokens is your budget? Reserve: 20% for the system prompt, 20% for the output, 60% for the dynamic context (documents, history, tools). ### Step 2: Prioritize context by relevance Include in this order: 1. Task instructions (always) 2. The most relevant documents or code (retrieved, not full codebase) 3. Relevant conversation history (not all history) 4. Supporting context (schemas, type definitions) Cut: long documents that contain 1 relevant paragraph, full file contents when only a function is needed, conversation history beyond the last N relevant turns. ### Step 3: Structure context for retrieval Agents pay more attention to the beginning and end of context. Put instructions at the top. Put the most relevant context closest to the task. ### Step 4: Use explicit context delimiters Mark different sections clearly: ``` <system>Your role and constraints</system> <documents>Retrieved content</documents> <task>What to do</task> ``` This prevents the model from confusing instructions with retrieved data. ### Step 5: Compress context aggressively Summarize long histories. Extract the relevant portions of long documents. Use structured data (JSON, tables) instead of prose where possible. ### Step 6: Monitor context quality Track: output quality vs. context length. If longer context is producing worse results, you have a context quality problem, not a context quantity problem. ## Verification Requirements - [ ] Context budget defined - [ ] Context prioritized: instructions → relevant docs → history - [ ] Long content compressed or chunked - [ ] Context sections delimited clearly - [ ] Output quality monitored relative to context composition