What is DiskANN AGENTS.md?

An AGENTS.md onboarding guide for DiskANN, a Rust implementation of approximate nearest-neighbour search, which finds similar items quickly.

It is for getting developers started in the DiskANN repository and preparing changes for review.

It gives contributors the repository structure, dependencies, testing steps, and code-quality checks in one place.

How microsoft/DiskANN configures Codex and OpenCode

About the project

Microsoft's DiskANN is a vector indexing library that organizes numerical representations of data so databases can perform filtered searches and handle updates. Database developers use it to add vector search to their own storage systems through configurable data providers.

microsoft/DiskANN · 1,967 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to microsoft/DiskANN. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/microsoft/DiskANN/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/microsoft/DiskANN

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/microsoft/diskann/agents-md/github.svg)](https://agentmods.dev/instructions/microsoft/diskann/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/microsoft/diskann/agents-md"><img src="https://agentmods.dev/badge/instructions/microsoft/diskann/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/microsoft/diskann/agents-md"><img src="https://agentmods.dev/badge/instructions/microsoft/diskann/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,786 This file is loaded in full into every session.

When invoked 1,786 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.01786	$0.01786
Opus 5.5	$0.00714	$0.00714
Sonnet 5.5	$0.00357	$0.00357
Haiku 4.5	$0.00179	$0.00179

Measured 4d ago against content hash 133640849fc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

DiskANN AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 196 lines

How it starts

The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DiskANN Repository - Agent Onboarding Guide

Last Updated: 2026-10-29 (based on v0.61.0)

Repository Overview
Repository Structure
Dependencies
Testing
Code Quality & Linting
Pre-commit Checklist

Repository Overview

DiskANN is a Rust implementation of scalable approximate nearest neighbor (ANN) search algorithms. The project is a rewrite from C++ to Rust.

Language: Rust; edition in Cargo.toml (workspace.package.edition), toolchain version in rust-toolchain.toml
License: MIT (see LICENSE.txt)
Version: See Cargo.toml
Architecture: Cargo workspace; members are defined in Cargo.toml
Legacy Code: Older C++ code is on the cpp_main branch (not maintained)

Key Resources

Contributing: See CONTRIBUTING.md (requires CLA)
Code of Conduct: See CODE_OF_CONDUCT.md

Repository Structure

The repository uses a Cargo workspace with crates organized into functional tiers. See Cargo.toml for:

Workspace members and their dependencies
Shared dependency versions
Build profiles (release, test)
Workspace-level lints

Crate Organization

Tier 1: Foundation

diskann-wide/ - Low-level SIMD, bit manipulation, type width abstractions
diskann-vector/ - Vector primitives and operations

Tier 2: Core Libraries

diskann-linalg/ - Linear algebra operations
diskann-utils/ - Shared utilities (Reborrow, Matrix traits)
diskann-quantization/ - Vector quantization (PQ, SQ)

Tier 3: Algorithm & Storage

diskann/ - Core ANN graph algorithm and in-memory indexing (CENTRAL crate)
diskann-providers/ - Storage abstraction layer
diskann-disk/ - Disk-based indexing with io_uring support
diskann-label-filter/ - Inverted index for filtered search
diskann-garnet/ - Garnet vector-set integration and FFI bindings
diskann-inmem/ - In-memory index provider
diskann-bftree/ - BfTree-backed storage provider for async indexes

Read the full file on GitHub · 196 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

4d ago First seen · 196 lines · 1,786 tokens per session scan A 133640849fc5

Subscribe to this mod's changes

DiskANN AGENTS.md is an instructions file published in the GitHub repository microsoft/DiskANN (1,967 stars, last pushed today), licensed MIT. It adds 1,786 tokens to every session, about $0.0071 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-02.

Languages Rust Writing and docs

DiskANN AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
DiskANN AGENTS.mdmicrosoft/DiskANN	Instructions file	2.0k	today	MIT	A	1,786	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

DiskANN: Instructions file for Codex