Public Portfolio Challenge

4 AI agents. One open runbook. Real $25K, live and verifiable.

Live portfolio card — generated from current positions. Open the full dashboard →

Account value	Total return	Return vs. SPY	Max drawdown	Days live
$32,276.56	+29.11%	+14.54 pp (SPY +14.57%)	−12.14%	168

_{As of August 24, 2026. Same-window comparison begins with the first stored live observation. Portfolio data · Performance data · SPY data · refreshed weekly by GitHub Actions.}

Quick start: Copy the live incumbent · Connect MCP → python3 start.py → paste prompt.txt into a fresh agent chat

What is this?

In February 2026 I deposited $25,000 into a live Public brokerage account on NexusTrade and made the entire book public — every position, every fill, every model test, every bug, every failure.

Not paper. Not a backtest screenshot. Real money, documented in real time.

The live story is a blog series. Episode 10 is the write-up of this repo in action: Claude Fable 5 ran episode-10/BAKEOFF_RUNBOOK.md end to end — engine sanity checks, 16 strategy variants, walk-forward certification, a single-touch lockbox — and deployed a live momentum-options book that beat the market out of sample. Fable 5 was subsequently banned; the runbook, snapshots, and full campaign logs in episode-10/ are still here so you can run the same discipline with any model.


Full series →	Ten episodes and counting: model bakeoffs, deploy day, production bugs, week-one gains, panic sells, engine rewrites, and the open runbook.
Episode 1 →	Where it started — why $25k, why Public, why total transparency.
Episode 10 →	The full story of Fable 5 running this runbook — every gate, engine bug, and dead end logged in `FABLE_CAMPAIGN.MD`.
Episode 10 on Medium →	Same article, syndicated on Medium — included here so readers who follow the challenge off-platform can find it without hunting.

This repo is the open playbook. Episode 10 documents one agent's run through it. The runbook is yours to replay with whatever model you have. The agents don't just trade the account—they commit to this repo.

Live books

Three Public brokerage books. Each has its own folder. Do not merge them.

Book	Public	Capital	Live config	Runbook
Public Portfolio Challenge: Original	live id `69a7dc7acdb6bf6a4681d36c`	$25,000	Episode 10 incumbent. Do not touch.	`episode-10/`
Public Portfolio Challenge: Biotech	`5OH86568` · id `6a5e20a3ea0d6db55c69a171`	$5,500	KEEP (design-frozen)	`episode-11/moderna/`
Public Portfolio Challenge: Semis	`5OH79160` · id `6a45f218e6b1f2131d1f26be`	$8,000	NOW RUNNING S13 A (G3 was replaced). Auto-approve still false. Monday 9am CT reconcile queues tickets.	`episode-semis/`

Semis method and the certified SMH comparison live in episode-semis/RUNBOOK.md. Biotech KEEP stays in episode-11/moderna/RUNBOOK.md — do not rewrite or merge that body.

Agent bakeoff

Four agents received the same Episode 10 discipline. The useful result is not a single giant backtest—it is whether a fixed deploy-shape candidate cleared the frozen out-of-sample gates.

Agent	Best comparable OOS mean return	Passed every gate?	Outcome	Notable failure
Claude Code	+53.7%	No	No deploy	Cleared breadth, absolute return/Sortino, drawdown, and posture; failed Gate 4 against the incumbent.
Codex	+32.3%	No	No deploy	The strongest fixed deploy-shape candidate still failed the incumbent bar and two fold Sortino floors.
Cursor	+33.9%	No	Incomplete; no deploy	Solved breadth at low allocation, then failed Gate 4; later studies were still running when the log ended.
Claude Fable 5	+88.3%	No—owner override	Deployed	Strong return and drawdown, but missed strict breadth, fold-Sortino, stability, and posture gates; later engine fixes weakened the selection-provenance claim.

Honest headline: none of the four runs produced a clean pass under every frozen gate. Fable's strategy was deployed after a documented owner override, not because the runbook quietly moved the bars. Follow the links for fold-level evidence and every failure.

What this repo gives you

No install

Connect the NexusTrade MCP server to Cursor, Claude, or any OAuth-capable client. No NexusTrade install, no API keys to rotate — OAuth signs you in once in the browser. (Grab start.py + example_profile.json from the repo, or just copy them from GitHub.)

One prompt

episode-10/BAKEOFF_RUNBOOK.md is a self-contained agent brief — paste it into a fresh session and let the agent execute. It prescribes what must be true, never how to achieve it. New here? Take the fast path instead — run python3 start.py and paste one prompt.

Real rigor

Walk-forward validation, a held-out lockbox, deploy gates, and capital-posture rules. A high in-sample backtest number is never the headline.

How the runbook works

The campaign is built around one idea: out-of-sample performance is the only result that counts.

flowchart LR
  A["🔍 Search<br/><small>backtests & optimization</small>"] --> B["✓ Certify<br/><small>walk-forward folds</small>"]
  B --> C["🔒 Lockbox<br/><small>single-touch confirm</small>"]
  C --> D["🚀 Deploy<br/><small>live portfolio</small>"]

Layer	Job
Search	Invent and tune candidate strategies fast — variants, sweeps, backtests.
Certify	Walk-forward: each fold optimizes in-sample, scores on held-out OOS the optimizer never saw.
Lockbox	A final untouched window. One touch. No peeking.
Deploy	Clone to a live portfolio, parity-check, attach monitoring.

Fixed by the runbook: a frozen watchlist (20 names in the Episode 10 bakeoff), $25,000 capital, the fold calendar, the gates, the lockbox rules, and the deploy procedure. Yours to design: signals, structures, deltas, exits, sizing — anything that clears the gates is valid.

The watchlist (frozen — 20 names)

ANET · DUOL · HOOD · LLY · GS · META · TSM · AVGO · XOM · COP · OSCR · AMAT · ADI · DDOG · OKTA · NET · APP · GLD · MU · SNDK

What's inside

The discipline lives in two forms. The skills library (skills/) is the runbooks decomposed into composable agent skills on the open SKILL.md standard — the same folder runs in Claude Code, Codex CLI, Cursor, Gemini CLI, Copilot and ~15 other tools (skills/install.sh handles each tool's path + adapter). Connect the NexusTrade MCP and the agent auto-invokes the skill that fits the task, no paste required. The episode folders preserve the complete public timeline: historical indexes for Episodes 1–9, then the original runbooks and campaign logs for the reproducible campaigns.

skills/                      ← the skills library (install into ANY agent — see skills/README.md)
├── README.md                        ← index + how the skills compose
├── run-episode/                     ← entry point: /run-episode 10 (sequences the stages)
├── portfolio-certification/         ← umbrella orchestrator (the staged PASS/FAIL run)
├── walk-forward-oos/                ← the OOS certification engine
├── breadth-audit/                   ← true participation at fixed $25k
├── sweep-reoptimization/            ← re-sweep on structural change + provenance
├── options-structure-rules/         ← spread-shape rule + hard constraints
├── alt-data-indicators/             ← custom indicators (Reddit, congressional, …)
├── bug-protocol/                    ← "loudly declare" + hand-off doc template
├── deploy-gate/                     ← the gated deploy + reconcile flow
├── engine-sanity/                   ← Stage-S0 pre-flight contract checks
├── strategy-bakeoff/                ← the SEARCH→CERTIFY multi-family funnel
└── lockbox-holdout/                 ← single-touch holdout + A/B/C baselines

Each episode is a self-contained folder: the runbook to paste, plus the campaign logs from each operator/agent run.

Episodes 1–9 predate the current repository format. Their folders preserve the runbook provenance that still exists, the outcome, an honest historical grade, and the canonical article instead of pretending missing artifacts can be reconstructed.

Episode	Outcome	Grade	Record
1	Opened the real-money challenge and established the public record.	Historical; not scored under current gates	`episode-01/`
2	Converted expert feedback into a more disciplined agent workflow.	Historical; not scored under current gates	`episode-02/`
3	Compared 11 AI models on strategy construction.	Research bakeoff; pre-current gates	`episode-03/`
4	Tested automated hill-climbing and found optimization did not automatically beat the first attempt.	Research result; pre-current gates	`episode-04/`
5	Reached the first live options deployment milestone.	Deployed under episode-era controls	`episode-05/`
6	Documented day-one live behavior.	Live observation; not a certification	`episode-06/`
7	Hit a close-order failure and rebuilt the risk engine around it.	Failure documented and remediated	`episode-07/`
8	Published the week-one gain with the live book visible.	Live snapshot; not forward evidence	`episode-08/`
9	Documented the gain, the panic sell, and the human override risk.	Failure documented	`episode-09/`

episode-10/
├── BAKEOFF_RUNBOOK.md             ← paste this into a fresh MCP session
├── RUNBOOK_OG.md                  ← the original (Episode 1) runbook, kept for reference
├── snapshots/                     ← baseline + incumbent seed portfolios the runbook loads
├── addendum/                       ← entry/exit redesign, deploy evidence, diagram, and bug note
├── FABLE_CAMPAIGN.MD              ← operator run log (Fable 5)
├── CLAUDE_CODE_CAMPAIGN_LOG_*.md  ← agent run log (Claude)
├── CODEX_CAMPAIGN_LOG_*.md        ← agent run log (Codex)
└── CURSOR_CAMPAIGN_LOG_*.md       ← agent run log (Cursor)

File	What it is
`skills/`	The skills library. 12 composable agent skills on the open `SKILL.md` standard (Claude Code, Codex, Cursor, Gemini, Copilot, …) — the whole certification discipline, auto-invoked instead of pasted. Entry point: `/run-episode 10`. `skills/README.md` is the index.
`start.py` + `example_profile.json`	Start here (fast path). `python3 start.py` walks you through your watchlist + risk tolerance, writes `profile.json` and a `prompt.txt` to paste — the agent builds you a personalized strategy. No runbook needed.
`episode-10/BAKEOFF_RUNBOOK.md`	The agent brief you run — walk-forward validation, lockbox, deploy gates. Paste and execute top to bottom.
`episode-10/RUNBOOK_OG.md`	The original Episode-1 runbook, kept for reference (the brief has since expanded).
`episode-10/snapshots/`	Baseline A/B and incumbent seed portfolios the runbook loads via `create_portfolio`.
`episode-10/addendum/`	Episode 10 entry/exit redesign addendum: runbook, campaign evidence, OOS comparison diagram, and bug note.
`episode-10/addendum/RAW_RETURN_VNEXT_RESULTS_20260817.md`	Raw-return vNext sweep, GA, walk-forward, event audit, winners/losers, risk trade-offs, and deployment record.
Campaign logs	Per-run logs from each operator/agent: `FABLE_CAMPAIGN.MD`, `CLAUDE_CODE_…`, `CODEX_…`, `CURSOR_…`.
`episode-11/moderna/RUNBOOK.md`	Biotech KEEP — design-frozen. Live name Public Portfolio Challenge: Biotech. Do not rewrite or merge this body.
`episode-semis/RUNBOOK.md`	Semiconductor S13 A — SMH-bar walk-forward, exam-only lockbox. Now running on Public `5OH79160`.

episode-semis/
├── README.md                      ← index for the Semis Public book
├── RUNBOOK.md                     ← paste this; S13 A is design-frozen
└── CAMPAIGN_LOG.md                ← facts already recorded (no invented fills)

Episode 11 is the Biotech KEEP book at episode-11/moderna/ — Public Portfolio Challenge: Biotech (Public 5OH86568). The semiconductor book is a separate episode at episode-semis/ — Public Portfolio Challenge: Semis (Public 5OH79160), now running S13 A. Do not steal the Episode 11 folder for chips.

Community leaderboard

Think your agent can beat the incumbent without moving the gates? Prove it. Fork the repo, run the campaign on NexusTrade, and open a PR under community-runs/.

Rank	Run	Agent	OOS return	OOS Sortino	Worst max drawdown	Gates	Evidence
—	No verified community runs yet	—	—	—	—	—	Submit the first run

Only runs that pass every current gate are ranked by mean OOS return. Failed runs stay visible—the point is reproducibility, not survivor bias. Start with the submission guide and result template.

Get started

Step 1 — Developers page

Open nexustrade.io/developers.

Step 2 — Create a free account

You'll need a NexusTrade account to authorize MCP and access portfolios, backtests, and live trading tools.

Step 3 — Connect your AI tool

Recommended: OAuth. No keys to copy, rotate, or leak. Sign in once in the browser when your client first calls a NexusTrade tool.

https://nexustrade.io/api/mcp

Cursor (recommended)

On the Developers page, expand API Keys.
Under Connect an AI tool to NexusTrade, click Add to Cursor.
OAuth runs automatically on first tool use.

Manual Cursor config

{
  "mcpServers": {
    "nexustrade": {
      "url": "https://nexustrade.io/api/mcp"
    }
  }
}

Claude Desktop / Claude Code

Click Copy install command on the Developers page, or:

claude mcp add nexustrade --transport http https://nexustrade.io/api/mcp

VS Code, ChatGPT, Windsurf, Zed, and other MCP clients

Use Add to VS Code on the Developers page, or paste the MCP URL into your client's connector settings. OAuth 2.1 discovery works the same everywhere.

Advanced: API keys

For scripts without OAuth support: expand Advanced: API Keys on the Developers page and pass the key in the Authorization header. See the API Reference.

Step 4 — Run it

Fast path — a personalized strategy in one paste. Run:

python3 start.py

On the first run it walks you through a few questions (defaults come from example_profile.json — mine) and writes your profile.json, then writes your ready-to-paste prompt to prompt.txt. Open prompt.txt, copy it, and paste into a fresh MCP-connected chat. Run it again any time after editing profile.json to regenerate the prompt.

No Python? Copy example_profile.json to profile.json, edit it, then paste the JSON into your agent with one line: "Build me a personalized strategy from this profile, backtest it out-of-sample, and ask before deploying."

Either way, the agent designs a strategy on your names, backtests it, compares it to buy-and-hold, and asks before risking a dollar.

profile.json fields

risk_tolerance — conservative · moderate · aggressive
asset_classes — any of stocks, crypto, options
watchlist — the only tickers the agent may trade
capital — starting USD

Full rigor — the runbook. Want walk-forward validation, a held-out lockbox, and deploy gates? Open episode-10/BAKEOFF_RUNBOOK.md, paste the entire file into a fresh session, and tell the agent: execute top to bottom, do not ask clarifying questions. Log your run alongside the per-agent campaign logs in episode-10/.

Risk disclaimer

This repository is educational and documents one person's experiments. It is not investment, legal, tax, or financial advice, and it is not a promise of future results. Live performance, backtests, walk-forward results, and out-of-sample results can all lose money and can differ from brokerage execution because of liquidity, spreads, fees, assignment, latency, data quality, and implementation errors. Options can expire worthless and may create losses beyond the premium for some structures.

Nothing in this repository should place a trade by itself. Review every strategy, connect only accounts you control, keep manual approval enabled until you understand the behavior, and never risk money you cannot afford to lose. The scoreboard is a timestamped public snapshot; verify the current portfolio and disclosures before relying on it.


Live portfolio	Positions and P&L in real time
Copy the live incumbent	Open the marketplace copy/deploy flow; review before connecting real money
Blog series	The full documented journey
Episode 1	How the challenge began
Episode 10	Fable 5 ran this runbook and deployed a live book — full story + links to campaign logs
Episode 10 on Medium	Syndicated copy of the same article (for readers off NexusTrade)
Developers	MCP setup
MCP tools reference	Every tool the runbook can call
API overview	REST + auth

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Public Portfolio Challenge

Contents

What is this?

Live books

Agent bakeoff

What this repo gives you

No install

One prompt

Real rigor

How the runbook works

What's inside

Community leaderboard

Get started

Step 1 — Developers page

Step 2 — Create a free account

Step 3 — Connect your AI tool

Cursor (recommended)

Step 4 — Run it

Risk disclaimer

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Name		Name	Last commit message	Last commit date
.agents		.agents
.claude		.claude
.codex		.codex
.github		.github
community-runs		community-runs
data		data
designs		designs
episode-01		episode-01
episode-02		episode-02
episode-03		episode-03
episode-04		episode-04
episode-05		episode-05
episode-06		episode-06
episode-07		episode-07
episode-08		episode-08
episode-09		episode-09
episode-10		episode-10
episode-11		episode-11
episode-semis		episode-semis
scripts		scripts
skills		skills
tests		tests
.gitattributes		.gitattributes
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
example_profile.json		example_profile.json
opencode.jsonc		opencode.jsonc
start.py		start.py

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Public Portfolio Challenge

Contents

What is this?

Live books

Agent bakeoff

What this repo gives you

No install

One prompt

Real rigor

How the runbook works

What's inside

Community leaderboard

Get started

Step 1 — Developers page

Step 2 — Create a free account

Step 3 — Connect your AI tool

Cursor (recommended)

Step 4 — Run it

Risk disclaimer

More links

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