Alphacouncil Agent

io.github.Zhao73由 GitHub 帳號 Zhao73 發布v1.0.15更新於 Oct 24, 2026

Simulated investment committee: 27 investor lenses read the same filings, debate, and a PM decides.

已驗證STDIO僅桌面金融AI 與機器學習

概覽

AI 產生的概覽

針對某檔標的執行模擬投資委員會:平行證據工作流程、方法席位、多空辯論,最後由投資組合經理給出結論。

可以做什麼
  • 把股票代號問題變成分階段研究流程:先蒐集公開來源證據,再由選定的投資方法席位解讀同一批帶日期的資料。
  • 執行多空雙方質詢,並由投資組合經理記錄決策、失效條件與可稽核存檔。
  • 先區分公司、ETF 與市場指數,讓 ETF 採持股穿透、指數採彙總方法論。
  • 可先做免金鑰的公開資料檢查(新聞與資料層),不啟動委員會工作流程。
  • 執行前選擇深度:快速,或 15、30、60 分鐘上限的完整等級。
  • 缺少的輸入、少數意見與反對報告都會保留為可見缺口與審閱素材。
適用情境
當你希望針對股票、ETF 或指數問題取得結構化、可審查的研究流程,而不是單一模型答案,並希望結論可追溯到來源編號、分歧被保留時適用。也適合在投入長時間執行前先做一次免費的公開資料檢查。
執行需求
以本機程序透過 stdio 執行,需要 Node.js 18 或更新版本。可透過 npm 套件或 Codex 外掛市集安裝,README 另說明 Claude Code、OpenCode、Grok Build 及 ChatGPT Work 開發者模式閘道。未宣告驗證、環境變數或標頭;首次資料檢查不需要資料供應商金鑰。僅限桌面端。
安裝前請注意
輸出是 AI 生成的方法模擬,不是投資建議,也不是經過驗證的模型;README 說明席位為 AI 撰寫的方法重構、尚待人工審閱,證據可能不完整或過時。執行會在本機執行目錄寫入產物。完整等級最長可達 60 分鐘並產生大量模型呼叫,可能帶來供應商費用。未經明確確認不會啟動執行。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Alphacouncil Agent,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。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[AlphaCouncil Agent]

An investment-research council you can inspect

One request becomes sourced evidence, competing method views, a bull/bear challenge, and a portfolio-manager verdict.

English · 中文 · 日本語

[build] [MIT] [node] [stars]

[OpenAI Codex] [Claude Code] [OpenCode] [Grok Build] [ChatGPT Work developer mode]

[MCP compatible] [Core data check needs no vendor key] [Zero runtime dependencies]

Install · Try the data layer · See how calls expand · Read a report

v1.7: concise setup with remembered choices, conclusions first, expanded daily history and full method-dependency checks. Fresh confirmation is still required. Upgrade details and data-source boundaries.

Question → sourced evidence → frozen method stances → Bull/Bear challenge → PM decision + saved audit

Historical UI recording (MP4) · Historical report artifact (SOX, Chinese)

The recording predates the current 26-seat candidate. It demonstrates an earlier interface only—not current timing, method fidelity, data accuracy, four-code-host validation, or ChatGPT Work validation.

One question. An inspectable case.

AlphaCouncil turns a ticker question into a reviewable research process. Parallel evidence workers gather public sources, selected investment-method seats interpret the same dated facts, bull and bear challenge the case, and a portfolio manager records the decision and its invalidation conditions. Missing inputs stay visible instead of being filled with guesses.

The same repository supports Codex, Claude Code, OpenCode, and Grok Build, plus a tool-only ChatGPT Work developer-mode gateway. It classifies companies, ETFs, and market indices before research so a basket is not analyzed as if it were an operating company.

Install in Codex

Prerequisite: Node.js 18 or newer. Install with these two shell commands:

bash
codex plugin marketplace add Zhao73/alphacouncil-agentcodex plugin add alphacouncil-agent@alphacouncil

Plugins load when Codex starts. Fully quit and restart Codex, open a new session, then enter this in the Codex composer:

text
@alphacouncil-agent analyze AAPL

For ChatGPT Work developer mode, Claude Code, OpenCode, Grok Build, Windows, troubleshooting, and the optional global npm command, use the complete install guide.

Free first run

Check the keyless public-data layer before starting a council:

text
# Codex@alphacouncil-agent AAPL news
# Claude Code, OpenCode, or Grok Build/alpha AAPL news

This check starts no council workers and requires no data-vendor key. For bounded research in Codex, use @alphacouncil-agent AAPL quick; on the three slash-command hosts, use /alpha AAPL quick.

Choose the depth before it runs

AlphaCouncil shows the work plan first. Full research asks separately for method seats, evidence breadth, and depth; the user confirms them before workers start. Full tiers use 15 / 30 / 60 minute ceilings—never a hidden token or currency estimate.

RunModel-call structureTime ceiling
Data checkKeyless tools only; no council workers and no additional model fan-outOutside the council tiers
Quick research4 evidence workers in parallel → 1–4 method seats in parallel → Bull and Bear in parallel → PM10 minutes
Full — fast8 core or exactly 11 all-scope evidence workers start together; each selected method stance is frozen deterministically before one isolated explanation worker; 3 debate rounds → PM15 minutes
Full — normalSame confirmed roster, frozen-stance sequence, 3 debate rounds, and PM, with a larger depth envelope30 minutes
Full — slowSame confirmed roster and stages with the largest depth envelope60 minutes

These are queue-to-terminal persistence ceilings, not measured completion times. They guarantee an explicit terminal record even when work is incomplete; a successful live fast run within 15 minutes has not yet been demonstrated across the four hosts. Fast keeps the full contract but uses an auditable stage-aware reasoning profile and one shared lifecycle budget per primary/retry/repair chain; retries cannot silently double a seat's cap.

When an instrument classification and typed-fact coverage are already available, the selector also shows an eight-family advisory method match derived from all 26 physical pack manifests. An explicit objective and holding horizon additionally calibrate the match and separate directional, non-voting risk, and context-only contributions; out_of_scope is never a negative vote. For a one-year directional request, the PM maps sourced base-case total return to one published rating rubric instead of counting conservative method seats; the server binds the frozen price/currency and recomputes that return from a same-currency target plus income. An out_of_scope seat remains visible in the method bench but is structurally absent from the PM rating path. It is only a prefill: every pack remains selectable, no run starts without explicit confirmation, and a missing classification produces no guessed default. The output represents AI-generated method simulations—not human experts, independent models, or a promise of profit. See method-panel recommendation and seat evidence.

Only the slow run with all methods and all evidence workers enables the additional verification path; the other full tiers do not claim that extra check.

What you gain

BenefitWhat it changes
A council, not one answerEvidence specialists, method seats, opposing cases, and a PM expose where agreement comes from.
A stance before the storyEach selected full-run method stance is fixed from structured inputs before its isolated explanation is written.
Claims you can traceMaterial report claims must point to source IDs; missing evidence remains a stated gap.
Disagreement that survives synthesisThree cross-examination rounds and persisted minority or opposing reports keep the losing case available for review.
The right research path for the assetCompanies use issuer evidence; ETFs use dated holdings look-through; indices use aggregate methodology. The first data check is keyless.

How the architecture differs

This compares workflow shapes, not named products. A particular tool may implement a different design.

Review concernSingle-model reply or common shared-context flowAlphaCouncil
Correlated errorsOne shared context can carry an early mistake into every later stepEvidence seats and opposing paths run in isolated workers; they may still use the same provider or model and are not independent models
Position formationThe position can be composed together with its explanationA structured stance is frozen before explanatory prose
Source traceTraceability depends on the prompt and hostEvery material claim is required to carry a source ID
Minority viewDissent can be folded into the final summaryMinority and opposing reports remain surfaced as review artifacts

What the seats are—and are not

The method-seat formulas are AI-authored reconstructions of published methods, pending human review. The named practitioners have not reviewed or endorsed these seats. They are not impersonations, independent models, or validated replicas. A stance is a structured argument to check against its inputs and sources—not a validated investment model.

Current source evidence boundary: 26 provisional method seats, 0 validated method models, 0/8 registered-and-completed canonical evaluation runs, and 0/4 live-host end-to-end runs. Passing source tests does not change those zeros.

Disclaimer

AlphaCouncil is for education and research only. It is not investment advice, a recommendation, or a solicitation. AI-generated analysis can be incomplete, outdated, or wrong. Verify the evidence yourself and consult a licensed professional before making an investment decision. The authors accept no liability for losses.

Go deeper

Runtime outputs are written outside the repository under ~/.alphacouncil-agent/runs/<run_id>/.

[AlphaCouncil]

Evidence first. Disagreement visible. Decisions reviewable.

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來源:README.md,提交 f8876d7

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版本歷史

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  1. v1.0.15最新Sep 16, 2026

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