LightAgent is a lightweight Python framework for building AI agents with tools, memory, guardrails, tracing, workflows, and collaboration between multiple agents. It supports developers who want reusable agent capabilities and OpenAI-compatible streaming interfaces.
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 skills add wanxingai/LightAgent --skill gupiaozhushougit clone --depth 1 https://github.com/wanxingai/LightAgentWrote 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/skills/wanxingai/lightagent/gupiaozhushou)<a href="https://agentmods.dev/skills/wanxingai/lightagent/gupiaozhushou"><img src="https://agentmods.dev/badge/skills/wanxingai/lightagent/gupiaozhushou/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/skills/wanxingai/lightagent/gupiaozhushou"><img src="https://agentmods.dev/badge/skills/wanxingai/lightagent/gupiaozhushou.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.00894 |
| Opus 5 | $0.00017 | $0.00447 |
| Sonnet 5 | $0.00007 | $0.00179 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
财经分析工具包 scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
bins: ["python", "curl"] What it actually says
财经分析工具包
专业的财经分析工具包，为AI Agent提供全面的财经分析能力。包含股票数据分析、市场趋势预测、投资组合优化等功能。
📊 功能模块
1. 股票数据分析
- 实时股票价格获取
- 历史数据查询与分析
- 技术指标计算（MA, RSI, MACD等）
- 基本面数据获取
2. 市场趋势分析
- 大盘指数监控
- 行业板块分析
- 市场情绪指标
- 宏观经济数据集成
3. 投资建议引擎
- 风险评估模型
- 投资组合优化
- 资产配置建议
- 止损止盈策略
4. 财经新闻聚合
- 实时财经新闻
- 热点事件分析
- 舆情监控
- 影响评估
🚀 快速开始
安装依赖
pip install yfinance pandas numpy matplotlib
基本使用示例
from finance_toolkit import StockAnalyzer
# 创建分析器
analyzer = StockAnalyzer()
# 获取股票数据
data = analyzer.get_stock_data("AAPL", period="1mo")
# 技术分析
analysis = analyzer.technical_analysis(data)
print(analysis)
📁 文件结构
finance-toolkit/
├── SKILL.md # 技能说明文档
├── README.md # 用户文档
├── finance_toolkit.py # 核心Python模块
├── stock_analyzer.py # 股票分析模块
├── market_trends.py # 市场趋势模块
├── investment_advisor.py # 投资建议模块
├── news_aggregator.py # 新闻聚合模块
└── examples/ # 使用示例
🔧 工具函数
股票分析工具
get_stock_price(symbol)- 获取实时股价get_historical_data(symbol, period)- 获取历史数据calculate_technical_indicators(data)- 计算技术指标analyze_fundamentals(symbol)- 分析基本面
市场分析工具
get_market_indices()- 获取大盘指数analyze_sector_performance()- 分析行业表现get_market_sentiment()- 获取市场情绪predict_market_trend()- 预测市场趋势
投资建议工具
assess_risk_profile()- 评估风险偏好optimize_portfolio(assets)- 优化投资组合generate_investment_advice()- 生成投资建议set_stop_loss_targets()- 设置止损止盈
📈 数据源
- Yahoo Finance (yfinance)
- 公开市场数据API
- 财经新闻API
- 宏观经济数据库
⚠️ 免责声明
本工具包提供的分析结果仅供参考，不构成投资建议。投资有风险，决策需谨慎。
🔗 相关资源
📝 更新日志
- v1.0.0 (2026-02-20): 初始版本发布，包含基础股票分析和市场趋势功能
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 122 lines · 35 tokens per session scan A db83ece53793
财经分析工具包 is a skill published in the GitHub repository wanxingai/LightAgent (1,217 stars, last pushed 6d ago), licensed Apache-2.0. It adds 35 tokens to every session and 894 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
risk-scoring
Score how concentrated and risky a portfolio is on a 0-100 scale from its position weights. Use when the user asks how risky their portfolio is, whether it is too concentrated, or for a diversification check.
valuation
Estimate whether a stock looks cheap or expensive using a price-to-earnings (P/E) based fair-value method. Use when the user asks if a stock is over- or under-valued, or for a fair-value / target price.
agent-framework-py-release
Use when cutting a Python release for the microsoft/agent-framework monorepo. Triggers on "bump py versions", "cut a python release", "prepare release PR for python", "release py packages", "bump python to X.Y.Z", or similar requests to bump Python package versions and prepare a release PR. Handles all four lifecycle…
python-package-management
Guide for managing packages in the Agent Framework Python monorepo, including creating new connector packages, versioning, and the lazy-loading pattern. Use this when adding, modifying, or releasing packages.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
verify-samples-tool
How to use the verify-samples tool to run, verify, and manage sample definitions in the Agent Framework repository. Use this when adding, updating, or running sample verification.