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.

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

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.

Related MCP server: deeplook

Install in Codex

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

codex plugin marketplace add Zhao73/alphacouncil-agent
codex 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:

@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:

# 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.

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

How the architecture differs

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

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

• Detailed English product, usage, tools, and architecture reference

• Complete four-host installation guide

• Report contract and complete example report

• Roadmap, security model, attribution, and changelog

• Local interfaces: npm run tui and npm run gui

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

Evidence first. Disagreement visible. Decisions reviewable.

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