Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/llmquant/quant-mind/agents-mdgit clone --depth 1 https://github.com/LLMQuant/quant-mindWhat 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 | $0.02189 | $0.02189 |
| Opus 5 | $0.01094 | $0.01094 |
| Sonnet 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 yesterday.
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.
- yesterday 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 (2,763 stars, last pushed 17d ago), licensed MIT. It adds 2,189 tokens to every session, about $0.0109 per session on Opus 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
spiceai copilot-instructions.md
Instructions for spiceai/spiceai, covering spice.ai agent instructions, data correctness — absolute top priority, evidence — no claim without a reproduction, build, test, lint (expensive — read first) and git & prs.
pipelex CLAUDE.md
Instructions for Pipelex/pipelex, covering pipelex coding rules, commands, linting, keyword-only arguments check and cleaning derived files.
awesome-quant AGENTS.md
AGENTS.md instructions for wilsonfreitas/awesome-quant, covering agents.md, project overview, architecture, commands and install deps (requires python 3.11+).
scout AGENTS.md
Instructions for agno-agi/scout, covering agents.md, project overview, architecture, contextprovider and one write surface.
moosestack copilot-instructions.md
Instructions for 514-labs/moosestack, covering moose repository guide, code standards, required before each commit, development flow and repository structure.
martex-quant CLAUDE.md
Instructions for martex-dev/martex-quant, covering session start — read these first, project instructions, ai trading bot project - master instructions, role and project objective.