Mekra Method
Knowledge finds its place.
Mekra lets AI decide how to organize your knowledge and use it to work with you.
From project documents to research, recipes, travel plans, and everyday notes.
Mekra Method keeps the reasons and conditions alongside your knowledge, so an agent can find the background it needs when you start a conversation.
Bring together meeting notes and customer commitments, research and experiment logs, study notes and weekly routines, or recipes and a weekly menu. Give AI the context to use them together.
Ask an AI agent that can read and edit the folder containing your material:
Formal release: Mekra Method 1.1 · Checked
Read the application guide in the release at https://github.com/mekra-lab/mekra-method/releases/tag/mekra-1.1 and apply it to this folder.
The agent decides how to organize and maintain knowledge from your material. After applying Mekra, you can ask it to incorporate new material into the existing Mekra.
Once setup is complete, ask the question you wanted these materials to help answer.
Not sure what to ask first?
Use the Mekra bundle in this folder as your starting point to understand these materials together, taking their context and relationships into account, and create the result that is most important and useful right now. Consider what emerges from the materials as a whole, and use your own judgment to decide what matters and how to use and present it. Create the result as a single HTML file that is easy to explore at a glance.
With the context in place, you can spend less time explaining and more time working together.
What to keep in your folder and what to ask, by field. The more your material keeps its reasons and conditions, the more an agent can find and use that context from a short request.
When the plan changes, ask the agent to record what changed and why. Your next check-in starts there.
When you agree on a new condition, ask the agent to add it to the customer commitments, not just the meeting notes. It becomes the basis for the next decision.
When a new result comes in, ask the agent to keep the earlier result and its conditions alongside it. You can follow how the interpretation changed.
When the design changes, ask the agent to update the design records with the reason, keeping the earlier decision.
Your material doesn't need particular names or formats. When you apply the method, the agent organizes it to fit.
AI understands what matters and why.Now it’s ready to work with you.
Mekra Method lets agents decide how to organize and maintain knowledge, then use that context in actual work. It provides application guides, templates, and operating knowledge to put the method into practice.
The method currently uses Open Knowledge Format (OKF) to represent knowledge. Its full principles, guides, and templates live in the public guide on GitHub.
Fewer instructions. Let agents find their own way.
A harness shapes how agents work through instructions, tools, and workflows.
Mekra provides context for judging what matters and why, and which conditions and relationships to consider.
Together, you can provide the structure agents need to act while leaving specific working methods to their judgment.
An ontology explicitly represents concepts and relationships.
Mekra lets agents judge what knowledge to keep, which reasons and conditions to connect, and what to update together when something changes.
Together, they can connect concepts and relationships expressed in an ontology with the reasons for that structure, the conditions where it applies, and the context of change.
Keep sources of truth clear, share context where it is needed, and delegate judgment.
Finding a fact is only part of understanding it. An agent also needs to know why it matters, when it applies, and what else changes with it.
Mekra keeps that context available where the agent needs it, and maintains the connections as your knowledge changes.
The method, its application materials, and its change history live on GitHub. This site introduces them; the repositories remain the source of truth.