Star200+

QuantMind

REVIEW · 71
Community indexed

QuantMind 开源版 是一款面向个人量化研究者的本地化金融量化交易平台，基于微软 Qlib 量化框架构建，提供从模型训练，回测，推理，实盘交易的完整研究闭环。 平台深度集成 LightGBM 等主流机器学习模型，支持 146 维量化因子训练与推理，用户可快速构建 Alpha 策略并在历史数据上验证效果。核心功能涵盖智能策略生成、模型训练、回测中心、QuantBot 助手及多模型管理，全部功能无使用限制。 开源版采用本地单机部署，通过 docker compose 一键启动，无需依赖云服务，数据与模型完全本地化，保障研究隐私。适合个人开发者、学术研究者及小团队进行量化策略原型验证与二次开发，是进入金融量化领域的理想起点。

Downloads0
Stars358
Version1.0.0
Quality80/100 · Strong
Trust71/100 · Sandbox only
Audit83/100 · Safe to try

Supply asset profile

Finance and quant workflows

Market data, SEC filings, portfolio analysis, quant research, backtesting, and risk workflows.

Browse track

Scenario

Finance and quant

I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add qusong0627/QuantMind

Maintenance

active

2mo since push

Risk

Safe to try

Quality score needs review

GitHub quality

358

80/100 Quality · 79/100 Trust

Coverage tags

FinanceFinance and quantquantanalysisdocker

Review notes

Quality score needs review

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Strong
80

Solid option that is likely worth shortlisting for production workflows.

Trust

Sandbox only
71

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Safe to try
83

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

PythonQuantCodexClaude CodeCursor

Stars

358 GitHub stars

Repo activity

358 stars, 114 forks

Maintenance

2mo since push

License

AGPL-3.0

Install

npx skills add qusong0627/QuantMind

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • Quality score needs review

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Finance and quant workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Retrieve market data

Suited agents

PythonQuantCodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add qusong0627/QuantMind
Policy
review
Human review
yes

Trust and risk

Trust
71/100
Audit
83/100
Risk level
Safe to try

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add qusong0627/QuantMind
Public auditEval reportResolve APIInstall handoff

Do not use when

  • teams that need a vendor-supported SLA
  • high-compliance environments without internal security review
  • No major risk signals from current metadata
  • Quality score needs review
  • Production credentials, payments, or irreversible account changes without explicit human review

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Agent safety v2

67/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • Quality score needs review

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add qusong0627/QuantMind

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Open JSON

/api/agent/resolve?task=Use%20QuantMind%20for%20an%20agent%20workflow&agent=codex&max_risk=medium

Resolve text

/api/agent/resolve?task=Use%20QuantMind%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text

Install handoff

/api/skills/qusong0627-quantmind/install

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use QuantMind in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20QuantMind%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/qusong0627-quantmind/install
Install command: npx skills add qusong0627/QuantMind
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Install handoff

/api/skills/qusong0627-quantmind/install

LLM text format

/api/skills/qusong0627-quantmind/install?format=text

Find alternatives

/api/skills/search?q=QuantMind&limit=3

Agent prompt

Use QuantMind for this task. Review https://www.openagentskill.com/api/skills/qusong0627-quantmind/install, then install with: npx skills add qusong0627/QuantMind

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Manifest

/api/registry/manifest/qusong0627-quantmind

LLM text

/api/registry/manifest/qusong0627-quantmind?format=text

Install alias

/api/registry/install/qusong0627-quantmind

Recommend

/api/registry/recommend?task=Use%20QuantMind%20in%20an%20agent%20workflow&limit=3

Agent fit

83/100

Finance and quant

Use-case tags

Finance and quantCoding agentsRAG and knowledge

Platforms

Python, Quant, Claude Code

Audit report

Safe to try · 83/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Companion skill for Finance and quant

Shortlist this skill and compare it with close alternatives before production adoption.

83
Readiness
Shortlist
Stage

Role in stack

Companion skill

Primary fit

Finance and quant

Trust label

Strong shortlist

Install path

Command ready

Use when

  • Finance and quant workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 80/100 quality profile
  • 16 OpenAgentSkill engagement events

review first

  • No major risk signals from current metadata

Implementation path

  1. 1Install it in a sandbox agent and run one Finance and quant task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

71
OpenAgentSkill Trust Score

GitHub adoption

INFO

358 GitHub stars

Stars/forks activity

INFO

358 stars, 114 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

2mo since push

License clarity

PASS

AGPL-3.0

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Quality score needs review
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Strong candidate for agent workflows

Solid option that is likely worth shortlisting for production workflows.

80
GitHub stars
358
Freshness
2mo ago
Install ready
Yes
License
AGPL-3.0

Workflow fit

Use this skill in these scenarios

Analyze markets

Finance and quant

I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.

Build and ship code

Coding agents

I need a coding agent that can understand a repository, edit code, and review pull requests.

Search private knowledge

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Workflow fit

Add it to a complete workflow

Turn skills into distribution

Content growth agent

A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.

Inspect, patch, and verify code

Coding review agent

A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.

Ingest, retrieve, and cite

RAG knowledge base

A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.

Alternative shortlist

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Overview

QuantMind 开源版 是一款面向个人量化研究者的本地化金融量化交易平台，基于微软 Qlib 量化框架构建，提供从模型训练，回测，推理，实盘交易的完整研究闭环。 平台深度集成 LightGBM 等主流机器学习模型，支持 146 维量化因子训练与推理，用户可快速构建 Alpha 策略并在历史数据上验证效果。核心功能涵盖智能策略生成、模型训练、回测中心、QuantBot 助手及多模型管理，全部功能无使用限制。 开源版采用本地单机部署，通过 docker compose 一键启动，无需依赖云服务，数据与模型完全本地化，保障研究隐私。适合个人开发者、学术研究者及小团队进行量化策略原型验证与二次开发，是进入金融量化领域的理想起点。

Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.

Platform compatibility

pythonFULL
quantFULL

Technical details

Version
1.0.0
License
AGPL-3.0
Last updated
Jun 16, 2026
Published
Jun 16, 2026

Frameworks & tools

PythonQuant

Decision snapshot

Companion skill

83
Ready
Shortlist
Stage

recent repository activity

Audit

Install review

Install and adoption review

83
Safe to try
Security
86/100
Maintenance
88/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
—
Recent failure
—
Outcomes
0
Output quality
—
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Agent-Proven rankingOutcome contract

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Compare AlternativesAuto-resolve PlanView on GitHubDocumentation

Growth loop

Share kit

X

Scenario-led draft for QuantMind, ready for a manual X post.

Curator note
A practical pick for market research:

QuantMind: QuantMind 开源版 是一款面向个人量化研究者的本地化金融量化交易平台，基于微软 Qlib 量化框架构建，提供从模型训练，回测，推理，实盘交易的完整研究闭环。 平台深度集成 LightGBM 等主流机器学习模型，支持 146 维量化因子训练...

358 stars

https://www.openagentskill.com/skills/qusong0627-quantmind?ref=x
Open X draft
Optional reply with install command
Listing + install path for QuantMind:
https://www.openagentskill.com/skills/qusong0627-quantmind?ref=x

Install: npx skills add qusong0627/QuantMind
Open reply draft

Listing source

Community indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
qusong0627
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Community indexed listing is attributed to qusong0627 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/qusong0627-quantmind?metric=listed&label=Listed)](https://www.openagentskill.com/skills/qusong0627-quantmind)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/qusong0627-quantmind?metric=trust&label=Trust)](https://www.openagentskill.com/skills/qusong0627-quantmind)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/qusong0627-quantmind?metric=audit&label=Audit)](https://www.openagentskill.com/skills/qusong0627-quantmind/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/qusong0627-quantmind?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/qusong0627-quantmind)
Preview badge Open audit Creator kit

Author

Q

qusong0627

@qusong0627

Tags

financequantanalysisdockerlightgbmpython3qlibpythongithub

Platform fit

Claude Code

Health signals

GitHub stars
358
Quality score
52/100
Last GitHub push
Jun 15, 2026
Framework hints
2
OpenAgentSkill views
14
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Sandbox only

71
  • GitHub adoption358 GitHub starsINFO
  • Stars/forks activity358 stars, 114 forks; issue activity unavailable in current metadataINFO
  • Recent maintenance2mo since pushPASS
  • License clarityAGPL-3.0PASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskexternal package install surfaceINFO

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