AIGCLIST
基准评分
Scalar Field 在 Agent 就绪度与 AI 可见性上的得分 AI 就绪度和 GEO Score 是 VibeLaunch 在提交后生成的平台评估。
决策摘要
Quantitative traders and self-directed investors seeking automated multi-strategy execution with alternative data integration
Automated multi-strategy portfolio management with scheduled execution, alternative data signals, and tokenized equity access
适合
- Automated quantitative trading with alternative data
- Institutional holdings mirroring and 13F tracking
- Event-driven strategy deployment with scheduled execution
注意
- Independent performance verification is not publicly available
- Specific brokerage venues and fee structures are not disclosed in documentation
- Pre-built strategies are vendor-operated with limited transparency into underlying models
概述
概览\nScalar Field 是一款革命性的交易终端，旨在通过能够思考、行动和适应的智能代理为金融专业人士赋能。它超越了传统的数据展示，提供自动化的洞察和行动，为用户在市场中提供显著优势。通过利用 AI，Scalar Field 将原始金融数据转化为可操作的情报，从而实现复杂的交易策略和深入的市场分析。\n\n## 什么是 Scalar Field？\nScalar Field 是一个提供机构级金融代理的高级平台。它旨在通过集成人工智能来自动化复杂的金融任务，从而重新定义交易终端。用户可以使用简单的英语指令与平台交互，访问并分析庞大的数据集，包括公司基本面、内部人士交易、经济指标和期权数据。\n\n## 核心优势\n- 自动化洞察：通过 AI 驱动的分析发现隐藏的模式和机会，从而获得竞争优势。\n- 可操作的情报：超越数据本身，通过可直接集成到交易策略中的自动化操作实现目标。\n- 自然语言界面：使用简单的英语指令与复杂的金融数据交互，使分析更加便捷。\n- 全面的数据集：访问广泛的金融数据，包括基本面、内部人士交易、经济指标和期权数据。\n\n## 主要功能\n该平台提供多项卓越功能：\n- AI 驱动的交易代理：分析市场、识别机会并执行操作的智能代理。\n- 回测能力：利用 AI 驱动的历史数据模拟来完善交易策略。\n- 事件驱动研究：利用突发新闻和市场公告触发的短期机会。\n- 宏观经济分析：分析全球趋势和经济预测，使策略适应市场转变。\n- 数据访问：全面访问超过 2,000 家公司的基本面数据、内部人士交易记录、超过 100 万个经济数据序列以及历史期权数据。
评价 (0)
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评分构成
编辑评分由哪些维度构成，每项附判断依据。 AI 就绪度和 GEO Score 是 VibeLaunch 在提交后生成的平台评估。
Information quality
Data types are well-specified — SEC Form 3/4/5, STOCK Act disclosures, 13F filings — and coverage metrics are provided (5,300+ tickers). However, data latency, accuracy, and sourcing methodology are not independently verified.
Documentation describes near real-time insider transactions, congressional disclosures, and institutional holdings with specific form references and ticker coverage counts.
Ease of use
Pre-built strategies lower the barrier to entry, and scheduled execution removes manual monitoring. However, undocumented brokerage support, opaque pricing, and Solana ecosystem requirements for tokenized equities add friction.
Strategies execute on fixed schedules without user intervention; documentation references brokerages and pricing but provides no specific names or fee tables.
Feature depth
The combination of isolated agent architecture, multi-strategy catalog, alternative data feeds, and tokenized equity access represents meaningful depth. Five distinct pre-built strategies and three alternative data categories exceed typical single-purpose trading tools.
Platform documents five named agentic ETF strategies, three distinct alternative data categories, tokenized pre-IPO and public equity trading, and point-in-time research data.
Workflow fit
Scheduled autonomous execution, per-agent isolation, and point-in-time research data align well with systematic trading workflows. The absence of API documentation or custom strategy authoring limits integration with existing quant stacks.
Strategies execute on fixed weekday schedules with automated reconciliation; agents maintain independent books; point-in-time data supports backtesting workflows.
Reliability
No independent performance audit, no publicly documented uptime SLA, no disaster recovery provisions, and no regulatory registration details. All strategy returns are vendor-reported, and execution depends entirely on vendor-operated infrastructure.
Platform publishes strategy descriptions and performance references but provides no third-party verification, compliance registrations, or operational reliability commitments in public documentation.
Value
Pricing is referenced but fee structures, credit costs, and trading commissions are not publicly disclosed. Without transparent cost data, value relative to alternatives cannot be assessed.
Documentation directs users to a separate pricing page for trading fees and credit pricing but provides no figures in public technical documentation.
评分反映可查证的产品资料，不代表实际使用效果保证。
Agent 就绪度
评估 Agent 能否通过产品的官方信息理解产品，并重建一条有文档依据的工作流程。
Automated agent-readiness assessment of https://scalarfield.io/: 4 of 22 checks verified across 2 fetched pages. No substantial machine interface is documented — agents can understand and cite the product but not operate it. Absent: agent_tooling_artifacts, api_reference, authentication, request_examples, response_examples, error_documentation.
就绪度维度
| 评估维度 | 得分 |
|---|---|
| 文档质量 | 50 |
| 执行结果可验证性 | 0 |
| 机器接口 | 0 |
| 项目定位清晰度 | 75 |
| 资源可发现性 | 100 |
| 工作流完整度 | 25 |
对 Agent 有帮助的部分
- docs: verified during this run
- llms txt: verified during this run
- sitemap: verified during this run
- quickstart: verified during this run
Agent 受阻的部分
- No agent instruction files, code-distribution commands, or named slash-command skills found across fetched pages.
- No api reference signal matched across 2 fetched pages.
- No authentication signal matched across 2 fetched pages.
- No request examples signal matched across 2 fetched pages.
- No response examples signal matched across 2 fetched pages.
- No error documentation signal matched across 2 fetched pages.
| 检查项 | 状态 | 详情 |
|---|---|---|
| 理解产品2/5 已核验 | ||
| 产品文档 | 已核验 | Developer/documentation pages reachable from the entry page (e.g. https://scalarfield.io/docs/introduction). |
| 快速开始 | 已核验 | Probe matched on https://scalarfield.io/docs/introduction: /quick ?start|getting started|in (five|5)/. |
| API 参考 | 未在本次官方来源链中找到 | |
| 请求示例 | 未在本次官方来源链中找到 | |
| 响应示例 | 未在本次官方来源链中找到 | |
| 连接接口0/4 已核验 | ||
| SDK | 未在本次官方来源链中找到 | |
| MCP 接口 | 未在本次官方来源链中找到 | |
| Webhooks | 未在本次官方来源链中找到 | |
| 认证文档 | 未在本次官方来源链中找到 | |
| 执行工作流0/6 已核验 | ||
| 命令行工具 | 未在本次官方来源链中找到 | |
| 非交互式命令 | 不适用于该产品 | No CLI was found to evaluate for this property. |
| 命令行结构化输出 | 不适用于该产品 | No CLI was found to evaluate for this property. |
| 结构化导入与导出 | 未在本次官方来源链中找到 | |
| 成功状态验证 | 未在本次官方来源链中找到 | |
| 智能体工具产物 | 未在本次官方来源链中找到 | |
| 维护与排错0/4 已核验 | ||
| 错误文档 | 未在本次官方来源链中找到 | |
| 速率限制 | 未在本次官方来源链中找到 | |
| 版本信息 | 未在本次官方来源链中找到 | |
| 更新日志 | 未在本次官方来源链中找到 | |
| 发现与验证2/3 已核验 | ||
| llms.txt | 已核验 | llms.txt published at the site root (78 lines). |
| 站点地图 | 已核验 | sitemap.xml reachable and lists site pages. |
| 智能体原生定位 | 未在本次官方来源链中找到 | |
官方证据
审计信息
- 评测时间
- 2026年8月30日
- 评测基准
- agent-readiness-v1
- 读取页面
- 2
- 来源深度
- 1
本审计从一个入口 URL 及其经过验证的官方来源链评估文档所支持的可操作性。AIGCLIST 未注册、登录、购买、执行或测试该产品的运行可靠性。
证据核查
关于该工具的公开声明，每条均标注核验状态与引用来源。
ai-agentic-trading已验证4scalarfield.io已验证核验于 2026年7月16日
Scalar Field is an AI agentic trading desk platform that enables automated strategy research, execution, and position management.
Each strategy agent operates with its own cash allocation, isolated position book, target-based order execution, reconciliation, and independent position management.
The platform provides point-in-time market data enabling timestamp-aligned historical research for strategy development and backtesting.
Platform documentation references supported brokerages and a dedicated pricing page but does not publicly disclose specific venue names, fee structures, or credit pricing in documentation.
https://scalarfield.io/ai-agentic-tradingscalarfield.io已验证3scalarfield.io已验证核验于 2026年8月30日
Scalar Field is an AI agentic trading desk platform that enables automated strategy research, execution, and position management.
The platform supports trading tokenized pre-IPO names via Jupiter on Solana, plus 48 tokenized public equities with full OHLCV and live pricing.
The entry page was fetched and analyzed for machine-interface signals (title, headings, developer links, keyword probes).
https://scalarfield.io/docs/market-data/overview已验证3scalarfield.io已验证核验于 2026年7月16日
Market data includes near real-time SEC Form 3/4/5 corporate insider transactions covering over 5,300 tickers derived from EDGAR filings.
Market data includes near real-time securities transaction disclosures by U.S. Senators and House Representatives under the STOCK Act.
Market data includes institutional holdings from quarterly SEC Form 13F filings.
https://scalarfield.io/docs/market-data/overviewagentic-etfs已验证2scalarfield.io已验证核验于 2026年7月16日
Scalar Field offers a catalog of pre-built agentic ETF strategies including SPY Heat Meter Momentum, India-born CEO Succession, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500, and Situational Awareness LP portfolio tracker.
Pre-built strategies execute on fixed weekday schedules — SPY Heat Meter Momentum at 10:00 AM ET and GPT-5.4 Multi-Signal S&P 500 rebalancing at 11:00 AM ET — with the latter ingesting technical indicators, real-time news sentiment, and macroeconomic data.
https://scalarfield.io/agentic-etfsagentic-etfs/india-born-ceo-succession-strategy已验证2scalarfield.io已验证核验于 2026年7月16日
Scalar Field offers a catalog of pre-built agentic ETF strategies including SPY Heat Meter Momentum, India-born CEO Succession, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500, and Situational Awareness LP portfolio tracker.
The India-born CEO Succession Strategy invests in U.S.-listed companies when a U.S.-born CEO is replaced by an India-born CEO — a transition the platform associates with historically strong long-term returns.
https://scalarfield.io/agentic-etfs/india-born-ceo-succession-strategyagentic-etfs/jane-street-13f-top-20-follower已验证2scalarfield.io已验证核验于 2026年7月16日
Scalar Field offers a catalog of pre-built agentic ETF strategies including SPY Heat Meter Momentum, India-born CEO Succession, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500, and Situational Awareness LP portfolio tracker.
The Jane Street 13F Top 20 Follower strategy reconstructs a portfolio from Jane Street's publicly disclosed quarterly holdings, selecting the top 20 U.S. stocks and ETFs by reported market value and excluding options positions.
https://scalarfield.io/agentic-etfs/jane-street-13f-top-20-followeragentic-etfs/open-ai-gpt-5-4-multi-signal-s-p-500-portfolio已验证2scalarfield.io已验证核验于 2026年7月16日
Scalar Field offers a catalog of pre-built agentic ETF strategies including SPY Heat Meter Momentum, India-born CEO Succession, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500, and Situational Awareness LP portfolio tracker.
Pre-built strategies execute on fixed weekday schedules — SPY Heat Meter Momentum at 10:00 AM ET and GPT-5.4 Multi-Signal S&P 500 rebalancing at 11:00 AM ET — with the latter ingesting technical indicators, real-time news sentiment, and macroeconomic data.
https://scalarfield.io/agentic-etfs/open-ai-gpt-5-4-multi-signal-s-p-500-portfoliohttps://scalarfield.io/llms.txt已验证1scalarfield.io已验证核验于 2026年8月30日
llms.txt is published at the site root and readable.
https://scalarfield.io/llms.txthttps://scalarfield.io/sitemap.xml已验证1scalarfield.io已验证核验于 2026年8月30日
sitemap.xml is reachable and lists site pages.
https://scalarfield.io/sitemap.xmlIntroduction - Scalar Field已验证1scalarfield.io已验证核验于 2026年8月30日
A documentation surface is reachable at https://scalarfield.io/docs/introduction.
https://scalarfield.io/docs/introductionagentic-etfs/situational-awareness-lp-leopold-aschenbrenner-portfolio-tracker已验证1scalarfield.io已验证核验于 2026年7月16日
Scalar Field offers a catalog of pre-built agentic ETF strategies including SPY Heat Meter Momentum, India-born CEO Succession, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500, and Situational Awareness LP portfolio tracker.
https://scalarfield.io/agentic-etfs/situational-awareness-lp-leopold-aschenbrenner-portfolio-trackerdocs/trading/overview已验证1scalarfield.io已验证核验于 2026年7月16日
Platform documentation references supported brokerages and a dedicated pricing page but does not publicly disclose specific venue names, fee structures, or credit pricing in documentation.
https://scalarfield.io/docs/trading/overview决策核对台
在依赖该产品或访问官网前，最值得先确认的问题。
Scalar Field is an AI agentic trading desk that lets users deploy strategy agents — each with its own cash allocation and isolated position book — across a catalog of pre-built agentic ETFs. It integrates alternative data including SEC insider transactions, congressional trading activity, and institutional 13F filings.
Each agent operates autonomously with isolated capital and positions, executing on a fixed weekday schedule. Agents reconcile against target allocations automatically and do not commingle funds with other strategies. Users select from pre-built strategies rather than coding custom logic.
The platform provides near real-time SEC Form 3/4/5 corporate insider transactions covering 5,300+ tickers, U.S. congressional trading disclosures under the STOCK Act, institutional holdings from quarterly 13F filings, and point-in-time historical data for research and backtesting.
Agentic ETFs are pre-built AI-managed portfolios that execute autonomously on fixed schedules. Examples include the SPY Heat Meter Momentum Strategy, Jane Street 13F Top 20 Follower, GPT-5.4 Multi-Signal S&P 500 Portfolio, and India-born CEO Succession Strategy.
Unlike robo-advisors that primarily allocate across broad asset classes, Scalar Field deploys isolated strategy agents with distinct investment theses — from momentum signals to insider-transaction tracking. Each agent has independent capital and execution logic, and the platform integrates alternative data sources not typically available in robo-advisory products.
Scalar Field's documentation references supported brokerages but does not publicly name specific venues. Users should contact the platform directly to confirm compatibility with their existing brokerage accounts before committing capital.
请在官网核验
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这些工具以带有明确编辑理由的替代关系关联到当前产品。
ASINCrate
Provides alternative data feeds and market intelligence that overlap with Scalar Field's insider-transaction and institutional-holdings data sources, though without the agentic trading execution layer.
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Browse AI
Offers general-purpose web automation that traders could use to scrape and monitor market data sources, but lacks Scalar Field's integrated strategy execution, position management, and pre-built agentic ETF infrastructure.
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