| name | toolkit-onboarding |
| plugin | toolkit-manager |
| description | Master onboarding coordinator and holistic portfolio bootstrap wizard for InvestmentToolkit. Guides new users through zero-config engine installation, account & pillar setup, broker/TradingView CDP ingestion, automated DCF baseline analysis, and live visual chart sync. Trigger on /toolkit-onboarding or "help me set up the toolkit" or "bootstrap my portfolio".
|
| allowed-tools | Bash, Read, Write |
Master Portfolio Bootstrap & Onboarding Wizard
Trigger: /toolkit-onboarding or /portfolio-bootstrap or "help me set up the toolkit"
🧭 Overview & Architecture
This master coordinator takes an investor from a clean repository clone directly to an institutional-grade, fully operating investment operating system:
[1. Pre-Flight Engine Check] ➔ [2. Accounts & Strategy Pillars] ➔ [3. Broker/TV Ingestion] ➔ [4. Automated DCF Baseline] ➔ [5. Live Chart Overlay & Launch]
🛠️ Step 1 — Zero-Config Engine & Plugin Installation
- Verify Runtime Prerequisites:
- Node.js 18.0+ (
node --version)
- Python 3.11+ (
python3 --version)
- Compile Virtual Environment & Dependencies:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
npm install --prefix investment_screener
npm ci --prefix tradingview-cdp
- Deploy & Reinstall All Plugins:
python3 .agents/skills/plugin-syncer/scripts/sync_with_inventory.py
- Initialize Private Data & Configuration Templates:
python3 -c "
import os, shutil
base = 'investment_screener/backend/data'
for f in ['cash_flows.json', 'portfolio-config.json']:
src = os.path.join(base, f + '.example')
dst = os.path.join(base, f)
if not os.path.exists(dst) and os.path.exists(src):
shutil.copy(src, dst)
print(f'Initialized: {f}')
"
🏛️ Step 2 — Conversational Account & Strategy Pillar Foundation
Guide the user through their core wealth architecture:
Checkpoint A: Account Architecture
Wizard Question 1:
"What investment account structure would you like to set up?"
- Option A (Recommended — Dual Account): TFSA (Primary ~75%) + RRSP (Mirror ~25%) with auto-mirroring.
- Option B (Single Account): Individual Taxable / Margin or TFSA only.
- Option C (Corporate / Trust): Custom multi-entity structure.
Checkpoint B: Core Strategy Pillars
Wizard Question 2:
"Let's establish your Core Strategy Pillars and target allocation weights (totaling 100%):"
- Option A (Recommended — High-Conviction Tech & Energy):
- ⚡ Power / Energy (
power): 25.0%
- 🧠 Compute / Hardware (
compute): 30.0%
- 🌐 Data Infrastructure (
datainfra): 20.0%
- 🚀 Software / Growth (
software): 15.0%
- 💵 Defensive Cash / Sourcing (
cash): 10.0% (via PSU-U.TO / BIL)
- Option B (Custom Allocation): Provide your custom pillars and percentages.
Idempotency & Execution:
Check if accounts/pillars are already seeded (SELECT COUNT(*) FROM strategy_pillar). If unseeded, execute the canonical seeding script:
python3 -c "
import sys, sqlite3
sys.path.insert(0, 'investment_screener/backend/py_services')
from domain_model.db_client import initialize_db
from domain_model.seed_real_accounts import seed_real_accounts
conn = initialize_db('investment_screener/backend/data/domain_model.sqlite')
seed_real_accounts(conn)
conn.close()
print('Accounts seeded successfully.')
"
🔄 Step 3 — Portfolio Ingestion & Cash Reconciliation
⚠️ CDP Pre-flight: Before importing live broker data, verify TradingView Desktop CDP connectivity by delegating to /tv-setup or running:
python3 plugins/tradingview/scripts/tv_health_check.py
Wizard Question 3:
"How would you like to import your active holdings and cash?"
- Option A (Recommended — Live TradingView Desktop CDP Sync): Open TradingView Desktop with your broker tab active (
--remote-debugging-port=9222) and run /tv-portfolio-sync. Automatically scrapes live share counts, market values, and cash into SQLite.
- Option B (Interactive Ticker Intake List): Provide a list of tickers (e.g.
STM, BE, PLTR, NVDA, CORZ) to onboard via /stock-intake.
- Option C (CSV / Snapshot Import): Import existing trade log from file.
📊 Step 4 — Automated Baseline DCF & Quality Sweep (Silent Batch Mode)
💡 Note: For onboarded holdings, Step 4 runs in Silent Batch Mode (non-interactive) to compute baseline DCF valuations and scores across all tickers without triggering multi-step conversational questionnaires per holding.
Iterate across all imported tickers in a background sweep:
- Fetch 5-year financials and transcript data via
fetch_financials.py {TICKER}.
- Calculate institutional health metrics (Rule of 40 Score and Piotroski F-Score).
- Generate Bear (20%), Base (50%), and Bull (30%) DCF projection scenarios (
projections/{TICKER}.json).
- Ingest research baselines into
intelligence.sqlite via record_intelligence_event.py.
🖥️ Step 5 — Visual Chart Overlay & Launch Application
- TradingView Visual Setup:
- Set active layout to
agent-layout.
- Inject
AI TA Levels v6 to render 21/50/200 EMAs + DCF Fair Value + Buy/Trim/Stop levels on the active chart.
- Launch the Full Suite:
python3 run_investment_toolkit.py
- React 19 Dashboard:
http://localhost:5173
- Node.js Express API:
http://localhost:3001
- TradingView CDP Bridge:
http://localhost:9222
- Run Initial Health Audit:
- Execute
/portfolio_health or /daily to confirm all green!
🎯 Master Bootstrap Summary Card
🎯 InvestmentToolkit Bootstrap & Portfolio Onboarding Complete!
Accounts Configured:
- TFSA (Primary): $[Total USD]
- RRSP (Mirror): $[Total USD]
Pillars Initialized:
- ⚡ Power / Energy: [XX]%
- 🧠 Compute / Hardware: [XX]%
- 🌐 Data Infrastructure: [XX]%
- 🚀 Software / Growth: [XX]%
- 💵 Defensive Cash: [XX]%
Active Holdings Onboarded: [N] tickers ($[Total Market Value])
Cash Sourced: $[Total Cash USD] ([N] sh PSU-U.TO)
DCF Projections Built: [N] tickers in domain_model.sqlite & backend/data/projections/
✅ React 19 Dashboard Live: http://localhost:5173
✅ TradingView CDP Visual Overlays Injected (AI TA Levels v6)
✅ Daily Loop Ready: Run /daily for your first morning triage
