QuantMind is a knowledge extraction and retrieval framework for quantitative finance that turns papers, news, and filings into structured, cited, time-aware financial knowledge. It supports quantitative researchers and downstream systems that need reliable financial information for retrieval and reasoning. Its catalogue add-ons help coding agents build and verify QuantMind workflows inside the repository.
Borrowing it
Nothing to install: this file belongs to LLMQuant/quant-mind. 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/LLMQuant/quant-mind/master/AGENTS.mdgit clone --depth 1 https://github.com/LLMQuant/quant-mindWrote 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/llmquant/quant-mind/agents-md)<a href="https://agentmods.dev/instructions/llmquant/quant-mind/agents-md"><img src="https://agentmods.dev/badge/instructions/llmquant/quant-mind/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/llmquant/quant-mind/agents-md"><img src="https://agentmods.dev/badge/instructions/llmquant/quant-mind/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 | $0.02189 | $0.02189 |
| Opus 5.5 | $0.00876 | $0.00876 |
| Sonnet 5.5 | $0.00438 | $0.00438 |
| Haiku 4.5 | $0.00219 | $0.00219 |
Grade A, and why
quant-mind 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 1mo 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QuantMind — Agent Instructions
Guidance for coding agents contributing to this repository. This file is the
single source of repository instructions; CLAUDE.md imports it verbatim, so
edit rules here, not there.
Start at contexts/CONTEXT_MAP.md, the navigation
index for contexts/. contexts/README.md is the
routing entry point for development or library-usage work.
Progressive Context Loading
Pages under contexts/ are agent-facing references designed for progressive
disclosure:
- Read lines 1-80 first. The preview contains
Quick SummaryandContentssections that explain the page's purpose, authority, and scope. - Use that preview to decide whether the page applies. Do not preload sibling pages or follow unrelated links.
- When a page applies, read the entire page before changing code, contracts, or repository guidance. The preview routes work; it does not replace the detailed contract.
- Follow directly linked canonical sources only as the task requires. Avoid deep reference chains and duplicate guidance in working context.
What This Is
QuantMind is a knowledge extraction and retrieval library for quantitative
finance, built on top of the OpenAI Agents SDK. It is a domain library,
not an agent framework: runtime, tracing, tool scaffolding, and multi-agent
handoff all come from openai-agents.
Positioning
QuantMind is an agent-native workbench for financial knowledge extraction —
its primary consumer is a coding agent working inside this checkout, not only a
human importing a package (workbench-first, library-second). Two engineering
dimensions structure it: context engineering (any source → typed, cited,
as-of-correct knowledge) and harness engineering (any agent → domain
specialist, via this repo's contracts, contexts/, skills, hooks, and
deterministic verify).
The canonical, always-current statement lives in
contexts/design/positioning.md.
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.
- 1mo ago First seen · 172 lines · 2,189 tokens per session scan A 1be3edf3424e
quant-mind AGENTS.md is an instructions file published in the GitHub repository LLMQuant/quant-mind (3,115 stars, last pushed 2mo ago), licensed MIT. It adds 2,189 tokens to every session, about $0.0088 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).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.