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DiskANN (Microsoft)

TOOL

Graph-structured indices for scalable, fast, fresh and filtered approximate nearest neighbor search. Handles billion-vector datasets on a single node with SSD-based indexing. MIT licensed

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Overview

DiskANN (Microsoft) is a free tool on OpenRuna. Graph-structured indices for scalable, fast, fresh and filtered approximate nearest neighbor search. Handles billion-vector datasets on a single node with SSD-based indexing. MIT l

What this tool does

"DiskANN (Microsoft)" is a tool you can copy, adapt, and run with any modern AI assistant. Graph-structured indices for scalable, fast, fresh and filtered approximate nearest neighbor search. Handles billion-vector datasets on a single node with SSD-based indexing. MIT licensed On OpenRuna it sits inside a connected graph of related tools, tools, and datasets, so branching into adjacent resources is one click away. Open a new conversation and paste it in, wire it into an agent, or keep it in your team's prompt library.

Use cases

  • Keep it in a shared library as the canonical version of this tool for your organisation.
  • Fork it as a baseline and layer in your own project context, constraints, and examples.
  • Hand "DiskANN (Microsoft)" to a new teammate so their tool output matches your team's quality bar from day one.
  • Use "DiskANN (Microsoft)" when you need a repeatable tool for professional work without rewriting instructions every time.

Example output

Ask the model to apply "DiskANN (Microsoft)" to your scenario and it returns a structured answer — clear sections, actionable steps, and assumptions stated upfront — ready to paste into docs, tickets, or code comments. Add one example of your own and the output quality jumps noticeably.

Tips by platform

Claude

Claude works best when you paste this tool up front and ask it to outline its plan before writing. Use the artifact panel to refine structured output turn by turn.

ChatGPT

ChatGPT responds well when you paste this tool and immediately give one concrete example of your input. Use a reasoning-capable model for multi-step work.

Cursor

In Cursor, lift the key instructions from this tool into .cursorrules or a SKILL.md file, then reference it in Agent mode with @ mentions. Keep the title in a comment so teammates can find it on OpenRuna.

Frequently asked questions

What is "DiskANN (Microsoft)"?
It is a tool listed on OpenRuna — Graph-structured indices for scalable, fast, fresh and filtered approximate nearest neighbor search. Handles billion-vector datasets on a single node with SSD-based indexing. MIT licensed You can copy and adapt it for ChatGPT, Claude, Cursor, or any other AI assistant.
Is "DiskANN (Microsoft)" free to use?
Most OpenRuna resources are open or CC0-licensed. Check the license shown on this page before commercial use; premium collections are clearly marked as such.
How do I get the best results from this tool?
Replace any placeholders, add your project context, and ask the model to confirm its assumptions first. Iterate over 2–3 follow-up turns rather than expecting a perfect first response.
Does "DiskANN (Microsoft)" work with both Claude and ChatGPT?
Yes — it is model-agnostic text, so it runs on Claude, ChatGPT, Gemini, and Cursor. The tips on this page cover each of those assistants specifically.
Where can I find resources related to "DiskANN (Microsoft)"?
Scroll to the Related resources section on this page, or open the matching category hub on OpenRuna to find connected prompts, tools, agents, and datasets in the same topic area.

Related resources