Framework: Context Engineering Checklist
A checklist for deciding what context a model actually needs, how to structure it, and what should be left out.
Use cases
Development & Code, Strategy & Planning, Research & Analysis
Platforms
Claude, GPT, Gemini, Model-Agnostic
Jump to a section
The resource
Copy and adapt. Do not paste blind.
For each workflow, define:
- task objective
- fixed rules
- dynamic context
- examples
- reference material
- memory requirements
- output contract
- review loop
Then remove any context that does not change the outcome.When to Use This
Use this when your prompts are bloated, your agents are inconsistent, or your team keeps stuffing entire documents into context windows and hoping.
It is useful for both single-prompt workflows and multi-step agents.
Why It Works
Context engineering is the discipline of deciding what information should travel with the task. This checklist turns that into a repeatable review.
The removal step is important. More context is not automatically better.
How to Customise
Break context into fixed and dynamic layers if the workflow repeats often.
Add retrieval logic notes if the system pulls external data into the prompt.
Limitations
It does not solve poor source material or weak workflow design by itself.
Some tasks still need experimentation to find the right context boundary.
Model Notes
Long-context models tolerate more information, but they still benefit from cleaner context structure.
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