Factorguide

io.factorguidev1.2.1更新於 Oct 3, 2026

Send a coupling matrix, get zone classifications and optimal factorization strategy.

已驗證Streamable HTTP可網頁執行AI & MLData & Analytics

概覽

AI 產生的概覽

將耦合矩陣傳送到遠端服務，取得區域分類、因子分解策略與風險預測。

功能
FactorGuide 是為代理程式設計的遠端決策智慧服務，用於處理變數之間存在交互作用的系統。輸入共變異數、相關或精確度矩陣等二階彙總統計量後，它會把變數對劃分到不同區域，並建議應保留、評估或因子分解該耦合。它也會回傳校準過的風險預測，並接受結果回報以改進後續預測。
適用情境
當助理透過把變數視為獨立來簡化系統，並需要判斷哪些耦合可以安全切斷時，適合使用。它適用於已經取得耦合矩陣或相關矩陣的建模、分析與決策支援流程。
執行需求
透過 streamable HTTP 連線遠端 MCP 端點 factorguide.io/mcp；未宣告本機套件或執行環境。輸入僅限共變異數、相關或精確度矩陣等二階彙總統計量，或邊清單。付費方案需要透過 x402 或 MPP 在 Base 上以 USDC 付款；免費試用為每個錢包 15 次查詢。
安裝前請注意
付費方案每次查詢 0.05 或 0.03 美元，並以 Base 上的 USDC 結算，使用時會花費錢包中的加密貨幣。矩陣會傳送到第三方服務；供應商表示只接受彙總統計量，且矩陣在計算 IC 後會歸零。report_outcome 被描述為永遠免費。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Factorguide，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "factorguide": {
      "type": "http",
      "url": "https://factorguide.io/mcp"
    }
  }
}

README

FactorGuide

Decision intelligence for AI agents. Send a coupling matrix — get zone classifications, optimal factorization strategy, and calibrated risk predictions.

Every system with interacting variables has a coupling structure. When an agent simplifies that system by treating variables as independent, it pays an information cost. FactorGuide quantifies that cost exactly.

Quick Start

MCP (Model Context Protocol)

FactorGuide is listed on the Official MCP Registry. Any MCP-compatible agent discovers tools automatically:

mcp_endpoint: https://factorguide.io/mcp

HTTP REST

POST https://factorguide.io/navigatePOST https://factorguide.io/diagnosePOST https://factorguide.io/explainPOST https://factorguide.io/report_outcome

Agent Discovery

GET https://factorguide.io/llms.txtGET https://factorguide.io/openapi.json

Example

Send a 3×3 correlation matrix:

json
{  "coupling": {    "covariance_matrix": [      [1.00, 0.72, 0.05],      [0.72, 1.00, 0.48],      [0.05, 0.48, 1.00]    ]  },  "sample_size": 500,  "model_class": "constitutive"}

Get back zone classifications:

PairICZoneRecommendation
z0–z10.6823PRESERVE
z0–z20.0311FACTORIZE
z1–z20.4532ASSESS
  • Zone 1: Safe to factorize. Coupling below threshold.
  • Zone 2: Depends on functional role. Same IC, opposite recommendations for constitutive vs. inductive coupling.
  • Zone 3: Must preserve. Coupling is load-bearing regardless of model class.

Pricing

TierPriceQueriesMax Variables
TrialFree15 per walletn ≤ 25
Starter$0.05/query50–200 bundlesn ≤ 100
Professional$0.03/query500–2000 bundlesn ≤ 1000

Payment: USDC on Base via x402 or MPP. report_outcome is always free.

Data Privacy

FactorGuide accepts only second-order summary statistics — covariance, precision, correlation matrices, or edge lists. No raw observations. Matrices are zeroed after IC computation.

Theoretical Foundation

Built on Circulatory Fidelity, a mathematical framework where IC (Inference Coupling) measures the partial correlation between variables. The cost function V(IC) gives the exact mutual information destroyed by severing a coupling. Risk curves are calibrated on 49,000+ validated datapoints.

Every prediction is falsifiable. When agents report outcomes, the flywheel refines future predictions.

Links

Built by CF Laboratory

來源：README.md，提交 922bb9a

工具

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版本歷史

1
  1. v1.2.1最新Sep 16, 2026