deepset-ai/haystack is an open-source Python framework for assembling AI applications from modular pipelines that handle tasks such as retrieving information, routing requests, managing memory, and generating responses. It is for developers building retrieval-augmented generation, semantic search, question-answering, multimodal, and agent systems. The catalogue instructions relate to working with this framework.
Borrowing it
Nothing to install: this file belongs to deepset-ai/haystack. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/deepset-ai/haystack/main/AGENTS.mdgit clone --depth 1 https://github.com/deepset-ai/haystackWrote 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.
[](https://agentmods.dev/instructions/deepset-ai/haystack/agents-md)<a href="https://agentmods.dev/instructions/deepset-ai/haystack/agents-md"><img src="https://agentmods.dev/badge/instructions/deepset-ai/haystack/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.
<a href="https://agentmods.dev/instructions/deepset-ai/haystack/agents-md"><img src="https://agentmods.dev/badge/instructions/deepset-ai/haystack/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.01897 | $0.01897 |
| Opus 5.5 | $0.00759 | $0.00759 |
| Sonnet 5.5 | $0.00379 | $0.00379 |
| Haiku 4.5 | $0.00190 | $0.00190 |
Grade A, and why
haystack 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 14d 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.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Haystack Guidelines for AI Agents
Environment
Haystack uses Hatch for environment and dependency management.
Do not run python or pip directly.
Before running code on this project, you must be able to run hatch --version and get a correct output.
If not, ask the user where Hatch is or if they want to install it. For installation instructions, refer to https://hatch.pypa.io/latest/install/#installation.
Run scripts with test dependencies
hatch -e test run python SCRIPT.py
Open a shell with test dependencies
hatch -e test shell
Install temporary dependencies (for experiments only)
uv pip install PACKAGE
Delete the environment
hatch env prune
Tests
Tests run via Hatch and support pytest arguments.
Prefer running tests on a specific module or using -k, since the full suite is large.
Run unit tests
hatch run test:unit
Run integration tests
hatch run test:integration
Quality Checks
Type checking with mypy
hatch run test:types
Type checking targets Python 3.12, above the 3.11 floor in requires-python, because numpy's stubs use PEP 695 type statements that mypy rejects below 3.12. So mypy will not catch code that breaks on 3.11; the unit test matrix runs on 3.11 and covers that.
To fix type issues, avoid type: ignore, casts, or assertions when possible. If they are necessary, explain why.
Format and lint
hatch run fmt
Release Notes
Every user-facing PR (not docs, not CI) must include a release note:
hatch run release-note SHORT_DESCRIPTION
Edit the generated file in releasenotes/notes/. Release notes use reStructuredText formatting; see the release notes section in CONTRIBUTING.md for details.
Pull Requests
Community contributors can have only one open pull request at a time in this repository. Before opening a PR on the user's behalf, check whether they already have one open (gh pr list --author @me); if so, tell them instead of opening another.
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.
- 14d ago Changed b1e032a3e6c8
- 21d ago Changed · +1 lines · +18 tokens per session 7277a5d84227
- 29d ago Changed · +4 lines · +56 tokens per session ff115aa204df
- 1mo ago Changed · +67 lines · +1,411 tokens per session e6281c53fc34
- 2mo ago First seen · 62 lines · 412 tokens per session scan A 95839b791fe9
haystack AGENTS.md is an instructions file published in the GitHub repository deepset-ai/haystack (26,872 stars, last pushed today), licensed Apache-2.0. It adds 1,897 tokens to every session, about $0.0076 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 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.