life. scored.

com.lifescored由 lifescored.com 發布官方發布者v1.0.0更新於 Oct 24, 2026

Rebuilds the scores real systems run on you — credit, actuarial, lending — in the open, cited.

已驗證Streamable HTTP可網頁執行金融資料與分析

概覽

AI 產生的概覽

一個遠端 MCP 伺服器,公開 life. scored. 的規則手冊與評分演算法,讓助理在本機計算生活評分,不向伺服器回傳任何資料。

可以做什麼
取得完整規則手冊:每條規則的權重、界線、證據標籤、來源與公式,以及引擎常數和輸入結構,助理據此在本機自行計算評分,不向伺服器回傳任何內容。僅取得需要向使用者蒐集的輸入欄位,含型別、範圍、允許值、預設值和淺白說明。閱讀評分方式的淺白解釋、其基本原則、刻意排除的內容以及隱私立場。了解如何透過 GitHub 建議更合理的權重、新來源或新規則。
適用情境
當使用者希望了解真實系統(信貸、精算、借貸)所產生評分的公開、有引用的拆解,或希望助理依其輸入在本機計算此類評分而不外傳資料時使用。也適合回答評分如何運作、是否公平之類的問題。
執行需求
遠端 Streamable HTTP 端點;無需身分驗證、API 金鑰、環境變數或請求標頭。助理依取得的規則手冊自行計算評分,因此無需傳送個人資料。
安裝前請注意
此伺服器為唯讀,不接受個人資料;README 說明不會向網站傳送任何關於個人的資訊。評分是對真實系統的公開重建,部分規則被標記為推測性而非有據可查,因此結果不應視為官方的信貸、精算或借貸決定。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 life. scored.,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。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.lifescored%2Fmcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "life-scored": {
      "type": "http",
      "url": "https://lifescored.com/mcp"
    }
  }
}

README

life. scored.

[deploy]

You are already a number.

A credit score, an actuarial row, a callback probability — this app rebuilds those numbers in the open: every rule cited or flagged as a guess, every weight visible and editable. Transparency, not judgment.

check it out - lifescored.com

Stack

  • Svelte 5 + SvelteKit, prerendered static pages, deployed to Cloudflare Workers
  • One dynamic endpoint: POST /api/narrative — KV-cached Gemini narratives with a deterministic local fallback (the app is fully functional with no API key at all)
  • All user data stays in the browser (localStorage + URL-fragment share links)
  • Traffic is measured with Cloudflare Web Analytics — cookieless and aggregate; it cannot see your inputs, which never leave your device anyway.

Develop

npm installnpm run dev      # app at localhost:5173 (narrative falls back to local composer)npm test         # vitest suite: rulebook invariants, engine, codec, worker handlernpm run check    # svelte-checknpm run types    # regenerate Cloudflare bindings after changing wrangler.jsonc

Narrative cache misses reserve one call atomically in the NarrativeBudget SQLite Durable Object: at most 200 per UTC day globally and 10 per IPv4 address or IPv6 /64 network per day. IPv4-mapped IPv6 shares the IPv4 allowance. People on the same network may share an allowance; cache hits and the local composer remain available. Failed upstream calls consume a reservation; failed reservations use the local fallback. Cache hits do not consume quota. The coordinator stores only a daily address hash, and removes previous-day entries on the next day's first reservation. It never sees profile inputs or narrative text. KV is used only for the narrative cache.

npm run build adds the Durable Object export to the adapter-generated Worker; deploy that build through the existing workflow. Wrangler creates the coordinator through the versioned migration in wrangler.jsonc. Run npm run types after binding changes; its helper resolves the class from source so checks work on a clean clone.

Deploy (Cloudflare free tier)

Deploys run automatically from GitHub Actions on every push to main (.github/workflows/deploy.yml): the workflow runs the full test suite + typecheck, and only then builds and deploys. Pull requests run the same gates and a Worker dry run without deploying.

One-time setup:

Secrets are kept in hush: stored once in your OS keychain, then piped straight into the consumer — they never get pasted into a terminal, echoed, or printed. This project's hush items use a lifescored- prefix so they group together in a keychain search. (No hush? Drop the hush pipe … -- prefix and run the bare npx wrangler / gh command; hush just wraps it.) Local dev needs no secrets at all — the narrative falls back to a local composer.

  1. Create the KV namespace and paste its id into wrangler.jsonc:

    npx wrangler kv namespace create NARRATIVE_KV
  2. Set the Gemini key as a Worker secret (persists across deploys; optional — omit to run AI-free with the local narrative fallback):

    hush set lifescored-gemini-key                                   # paste it once, hidden dialoghush pipe lifescored-gemini-key -- npx wrangler secret put GEMINI_API_KEY
  3. Give GitHub Actions the deploy credentials (Settings → Secrets and variables → Actions):

    hush set lifescored-cloudflare-api-token                         # "Edit Cloudflare Workers" tokenhush pipe lifescored-cloudflare-api-token -- gh secret set CLOUDFLARE_API_TOKENgh secret set CLOUDFLARE_ACCOUNT_ID --body "<your-account-id>"    # account id isn't secret

Push to main and the action ships it. To deploy by hand instead:

   npm run deploy

Deploy your own

Fork the repo, do the one-time setup above with your own Cloudflare account, and push. The app is fully functional with no Gemini key at all.

Editing the rulebook

Rules live in src/lib/rulebook/<domain>.ts. Each rule is declarative: logic, evidence tag (SOURCED/SPECULATIVE), citation with access date, a pure position(inputs) (the measured fact, normalized to a numeric position), declared bounds (negative floors only where the cited system itself subtracts; the wealth rules are uncapped above), and a weightRationale justifying its weight against the 1.0× income baseline; the engine computes points = round(position × weight). Add a rule, and the UI, weight editor, share codec, and about-page source list pick it up automatically. npm test enforces the invariants (bounds, integer scores, citation present).

Use it from an agent (MCP or skill)

The whole rulebook + exact math is published so any agent can compute a score on its own side — nothing about a person is ever sent to lifescored.com.

  • MCP server — com.lifescored/mcp on the official registry; endpoint https://lifescored.com/mcp (stateless Streamable HTTP, no auth, accepts no personal data). Tools: get_rulebook, get_input_schema, get_methodology, how_to_give_feedback.
  • Skill — a drop-in skills/lifescored/ skill. Copy it into your agent's skills directory (e.g. ~/.claude/skills/). It prefers the MCP and falls back to rules.json.
  • Raw data — https://lifescored.com/rules.json and /llms.txt.

Contributing

Every commit must reference a GitHub issue number, e.g. feat: add presets (#2) or refs #5. A commit-msg hook enforces this automatically — it is installed via core.hooksPath pointing to .githooks/, which activates on npm install (the prepare script runs git config core.hooksPath .githooks). Merge commits and reverts are exempt. To find or open an issue: gh issue list / gh issue create.

License

MIT — see LICENSE.

來源:README.md,提交 8573c81

工具

4

get_rulebook

Get the full rulebook + math

The complete life-score rulebook and exact math: every rule (weight, bounds, evidence, source, formula), the input schema (what to ask the user), and the engine constants. Use this to compute a score on your OWN side — nothing is sent back.

無需輸入參數。

get_input_schema

Get the questions to ask

Just the fields to collect from the user, with types, ranges/allowed values, defaults, and plain-language help. Ask only for what you do not already know; missing fields fall back to their default.

無需輸入參數。

get_methodology

How the scoring works

Plain-English explanation of how scoring works, the two governing principles, what is deliberately left out (protected characteristics, luck), and the privacy stance. Use to answer "how does this work / is this fair" questions.

無需輸入參數。

how_to_give_feedback

How to propose an improvement

How to suggest a better weight, a fresh source, or a new rule via GitHub, so improvements from many people aggregate in the open.

無需輸入參數。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分