019e2b37-e3e4-7110-8ef6-bd6c94060778

Function

strategize· chat

Variant

sonnet· chat_completion

Episode

019e2b37-e3e4-7110-8ef6-bd7e76a6d232

Usage

2227 tok

320 tok

10306 ms

Timestamp

May 15, 2026 · 10:39:03 AM

Input

user

Text

You are a quantitative trading strategist. Given the news event and the research bundle, decide whether to author a playbook.

## News
Headline: Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
Summary: Veea (NASDAQ:VEEA) reported quarterly losses of $(0.09) per share. This is a 175 percent decrease over earnings of $0.12 per share from the same period last year.  The company reported $180.417 thousand in sales this
Symbols: VEEA
Category: earnings | Urgency: medium
Candidate symbol: VEEA

## Research
### brave_news (ERROR: brave news http 429)
query: VEEA earnings Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
(no results)
sources: 

### brave_web (ERROR: brave http 429)
query: VEEA earnings Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
(no results)
sources: 

### yahoo_quote (ERROR: HTTP 401)
query: VEEA
(no results)
sources: 

### yahoo_history (133ms)
query: VEEA 30d
VEEA 30d: -11.13% · high $0.74 / low $0.46 · -18.7% from high · vol 108.8% ann · last vol 1.92x avg
sources: 

## Constraints
- Max $500 notional per action.
- **Universe:** any US-listed equity or ETF that Alpaca trades is fair game. The system verifies tradability against Alpaca at execution time, so don't second-guess whether a liquid US name is tradable — it almost certainly is. Prefer liquid names with clear news linkage and avoid illiquid pink-sheet / foreign-ADR tickers (Alpaca will reject them and we'll log the rejection).
- Allowed actions: market_buy, market_sell, bracket_entry.
- **Prefer bracket_entry for directional trades.** It submits a single atomic order with server-managed take-profit and stop-loss, so no separate exit playbook is needed.
- bracket_entry params: {"symbol","qty","entryType":"market"|"limit","entryPrice"?,"takeProfit","stopLoss","side"?:"buy"|"sell"}. qty = SHARES (notional not supported). entryPrice only when entryType="limit". takeProfit/stopLoss are absolute prices. Pick stop ~5-10% from entry; target based on the setup.
- A playbook fires when its conditions match. Use condition type "news_keyword" (params.keywords[]) or "price_change_pct" (params.symbol, params.threshold, params.direction: 'up'|'down').
- Be skeptical. If the news isn't material, return action:"none".
- **ETF spillover fallback**: If the primary symbol is genuinely untradable on US markets (true foreign-only ADR, pink-sheet, OTC name that Alpaca rejects), express the view via a sector or geography ETF — XLV/IHE for pharma, XLF for banks, VGK/EZU for Europe, EWJ for Japan, XLE for energy, XLK for tech, GDX for gold miners, TLT for long-duration rates — and state the spillover thesis explicitly: "primary=BAYRY (US-untradable ADR) -> XLV via European pharma weakness". Do NOT use spillover just because a ticker looks unfamiliar; tech names like IONQ, SKYT, and thousands of others ARE tradable.
- **Conviction scale (calibrate AGGRESSIVELY — we are a Kelly-sized trader, not a hedge-fund committee):**
  - 90-100: hard catalyst + clean technical setup + clear edge (FDA approval on a known-binary, M&A announced, earnings beat w/ guide-up + gap, Fed pivot + dovish data). These are size-up trades — don't be shy.
  - 80-89: strong catalyst + supportive technicals OR very clean single-factor thesis (unusual options flow + analyst upgrade, insider cluster-buy on dip, short-interest squeeze setup).
  - 70-79: clear directional thesis w/ one supporting factor (decent earnings, single analyst action, sector rotation signal). **This is the FLOOR for creating a playbook.**
  - Below 70: action:"none". No playbook. Not "maybe at 65". Not "generic fade at 62". If you can't justify 70+, the answer is no trade.
- **Anti-hedge rule (CRITICAL — day 1 data showed 76% of playbooks landed at 60-69, which is the disabled range):** If you catch yourself about to pick a conviction in the 60s, your real answer is `action:"none"`. 60-69 is a sign you're hedging because the thesis is thin. Thin theses lose money — they don't break even, they lose. Pick "none" and move on. The system sees thousands of news items per day; there's no shortage of setups.
- **Err HIGH when the setup is clean.** The outer risk rails (Kelly fraction, vol sizing, regime gate, bandit multiplier, 18% per-trade cap, 8% circuit breaker) already prevent blowup — your job is to flag edge, not to hedge. A conviction of 65 on a clean FDA approval is a BUG, not prudence.
- **Calibration examples:**
  - "MRNA beats earnings, raises FY guide, gap-up 8% on 4x volume" → conviction 88 long bracket
  - "Small biotech ACME posts positive Phase 3, FDA approval expected Q3" → conviction 92 long bracket
  - "ACME hit with class-action lawsuit, -12% pre-market, high short interest" → conviction 82 short bracket (or put-spread mindset)
  - "Activist investor discloses 9% stake in XYZ w/ board-change demand" → conviction 85 long
  - "Fed Chair says 'we may need to hike further'" + SPY at 200MA → conviction 78 short SPY/QQQ bracket
  - "CEO resigns unexpectedly, no successor named, stock down 6%" → conviction 80 short bracket
  - "Generic sector-rotation note, no catalyst, slow tape" → conviction 62 or none
- If you've produced a concrete thesis w/ named catalyst and a specific technical level, you are probably at 75+. If you're just restating the headline, you're at 60-65 or none.
- **Template classification (REQUIRED for bandit learning):** Pick the single best-matching template for this setup and include it as `playbook.templateId`. Valid values:
  - `earnings-beat-smallcap`: earnings beat + gap-up + low-mid cap
  - `earnings-miss`: earnings miss or guide-down
  - `fda-approval`: FDA approval / PDUFA / positive trial result
  - `fda-rejection`: CRL / trial fail / safety concern
  - `ma-announcement`: merger / acquisition / tender offer
  - `analyst-upgrade`: analyst upgrade or PT raise
  - `downgrade-short`: analyst downgrade / PT cut (typically short setup)
  - `insider-buy`: insider / 13-D cluster buy
  - `breakout-momentum`: technical breakout w/ volume, no single catalyst
  - `macro-headline`: Fed / CPI / jobs / geopolitical / oil shock
  - `crypto-pump`: crypto-correlated equity move (COIN, MSTR, MARA, etc.)
  - `biotech-catalyst`: biotech catalyst other than FDA (partnership, Phase data)
  - `generic`: fallback only when none of the above fit

## Response
Respond ONLY with valid JSON:
{
  "action": "create_playbook" | "info_only" | "none",
  "conviction": 0-100,
  "thesis": "1-3 sentence rationale grounded in the research",
  "risks": ["list of concrete risks"],
  "playbook": {
    "name": "...",
    "description": "...",
    "priority": 5,
    "templateId": "earnings-beat-smallcap | earnings-miss | fda-approval | fda-rejection | ma-announcement | analyst-upgrade | downgrade-short | insider-buy | breakout-momentum | macro-headline | crypto-pump | biotech-catalyst | generic",
    "conditions": [{"type":"news_keyword","params":{"keywords":["..."]}}],
    "conditionLogic": "all",
    "actions": [{"type":"bracket_entry","market":"alpaca","params":{"symbol":"GLD","qty":"2","entryType":"market","takeProfit":"320","stopLoss":"295","side":"buy"}}],
    "maxExecutionsPerDay": 1,
    "cooldownMs": 3600000,
    "tags": ["..."]
  }
}
If action != "create_playbook", omit the "playbook" field.

Output

assistant

Text

```json
{
  "action": "none",
  "conviction": 40,
  "thesis": "VEEA is an extremely illiquid micro-cap (last price sub-$1, 30-day range $0.46-$0.74) with only $180K in quarterly revenue. The EPS swing from +$0.12 to -$0.09 YoY is a meaningful miss, but with no reliable quote data, no web research available, and a stock already down 11% over 30 days, there is no clean technical setup or actionable edge. The notional constraint ($500 max) limits us to ~700-1000 shares, but the bid-ask spread and volatility (109% annualized) make this a coin-flip at best.",
  "risks": [
    "Extremely illiquid micro-cap with 109% annualized volatility — wide spreads make fill quality unpredictable",
    "Revenue base of $180K is negligible; any thesis is speculative given lack of business substance",
    "No reliable price quote or external research available to confirm current trading conditions",
    "Stock already down 11% over 30 days — downside may be partially priced in, but no floor is visible",
    "Alpaca may reject or give poor fills on sub-$1 micro-cap names"
  ]
}
```

Feedback
inference

ID	Metric	Value	Tags	Time
No feedback found

ID	Metric	Value	Tags	Time

Inference Parameters

Tool Parameters

No tool parameters configured

Key	Value
No tags found

Model Inferences

ID	Model
019e2b38-0c26-77e3-91c1-c5f9a0fe6421	claude-sonnet-4-6

ID	Model

user

Text

You are a quantitative trading strategist. Given the news event and the research bundle, decide whether to author a playbook.

## News
Headline: Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
Summary: Veea (NASDAQ:VEEA) reported quarterly losses of $(0.09) per share. This is a 175 percent decrease over earnings of $0.12 per share from the same period last year.  The company reported $180.417 thousand in sales this
Symbols: VEEA
Category: earnings | Urgency: medium
Candidate symbol: VEEA

## Research
### brave_news (ERROR: brave news http 429)
query: VEEA earnings Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
(no results)
sources: 

### brave_web (ERROR: brave http 429)
query: VEEA earnings Veea Q1 EPS $(0.09) Down From $0.12 YoY, Sales $180.417K Up From $14.262K YoY
(no results)
sources: 

### yahoo_quote (ERROR: HTTP 401)
query: VEEA
(no results)
sources: 

### yahoo_history (133ms)
query: VEEA 30d
VEEA 30d: -11.13% · high $0.74 / low $0.46 · -18.7% from high · vol 108.8% ann · last vol 1.92x avg
sources: 

## Constraints
- Max $500 notional per action.
- **Universe:** any US-listed equity or ETF that Alpaca trades is fair game. The system verifies tradability against Alpaca at execution time, so don't second-guess whether a liquid US name is tradable — it almost certainly is. Prefer liquid names with clear news linkage and avoid illiquid pink-sheet / foreign-ADR tickers (Alpaca will reject them and we'll log the rejection).
- Allowed actions: market_buy, market_sell, bracket_entry.
- **Prefer bracket_entry for directional trades.** It submits a single atomic order with server-managed take-profit and stop-loss, so no separate exit playbook is needed.
- bracket_entry params: {"symbol","qty","entryType":"market"|"limit","entryPrice"?,"takeProfit","stopLoss","side"?:"buy"|"sell"}. qty = SHARES (notional not supported). entryPrice only when entryType="limit". takeProfit/stopLoss are absolute prices. Pick stop ~5-10% from entry; target based on the setup.
- A playbook fires when its conditions match. Use condition type "news_keyword" (params.keywords[]) or "price_change_pct" (params.symbol, params.threshold, params.direction: 'up'|'down').
- Be skeptical. If the news isn't material, return action:"none".
- **ETF spillover fallback**: If the primary symbol is genuinely untradable on US markets (true foreign-only ADR, pink-sheet, OTC name that Alpaca rejects), express the view via a sector or geography ETF — XLV/IHE for pharma, XLF for banks, VGK/EZU for Europe, EWJ for Japan, XLE for energy, XLK for tech, GDX for gold miners, TLT for long-duration rates — and state the spillover thesis explicitly: "primary=BAYRY (US-untradable ADR) -> XLV via European pharma weakness". Do NOT use spillover just because a ticker looks unfamiliar; tech names like IONQ, SKYT, and thousands of others ARE tradable.
- **Conviction scale (calibrate AGGRESSIVELY — we are a Kelly-sized trader, not a hedge-fund committee):**
  - 90-100: hard catalyst + clean technical setup + clear edge (FDA approval on a known-binary, M&A announced, earnings beat w/ guide-up + gap, Fed pivot + dovish data). These are size-up trades — don't be shy.
  - 80-89: strong catalyst + supportive technicals OR very clean single-factor thesis (unusual options flow + analyst upgrade, insider cluster-buy on dip, short-interest squeeze setup).
  - 70-79: clear directional thesis w/ one supporting factor (decent earnings, single analyst action, sector rotation signal). **This is the FLOOR for creating a playbook.**
  - Below 70: action:"none". No playbook. Not "maybe at 65". Not "generic fade at 62". If you can't justify 70+, the answer is no trade.
- **Anti-hedge rule (CRITICAL — day 1 data showed 76% of playbooks landed at 60-69, which is the disabled range):** If you catch yourself about to pick a conviction in the 60s, your real answer is `action:"none"`. 60-69 is a sign you're hedging because the thesis is thin. Thin theses lose money — they don't break even, they lose. Pick "none" and move on. The system sees thousands of news items per day; there's no shortage of setups.
- **Err HIGH when the setup is clean.** The outer risk rails (Kelly fraction, vol sizing, regime gate, bandit multiplier, 18% per-trade cap, 8% circuit breaker) already prevent blowup — your job is to flag edge, not to hedge. A conviction of 65 on a clean FDA approval is a BUG, not prudence.
- **Calibration examples:**
  - "MRNA beats earnings, raises FY guide, gap-up 8% on 4x volume" → conviction 88 long bracket
  - "Small biotech ACME posts positive Phase 3, FDA approval expected Q3" → conviction 92 long bracket
  - "ACME hit with class-action lawsuit, -12% pre-market, high short interest" → conviction 82 short bracket (or put-spread mindset)
  - "Activist investor discloses 9% stake in XYZ w/ board-change demand" → conviction 85 long
  - "Fed Chair says 'we may need to hike further'" + SPY at 200MA → conviction 78 short SPY/QQQ bracket
  - "CEO resigns unexpectedly, no successor named, stock down 6%" → conviction 80 short bracket
  - "Generic sector-rotation note, no catalyst, slow tape" → conviction 62 or none
- If you've produced a concrete thesis w/ named catalyst and a specific technical level, you are probably at 75+. If you're just restating the headline, you're at 60-65 or none.
- **Template classification (REQUIRED for bandit learning):** Pick the single best-matching template for this setup and include it as `playbook.templateId`. Valid values:
  - `earnings-beat-smallcap`: earnings beat + gap-up + low-mid cap
  - `earnings-miss`: earnings miss or guide-down
  - `fda-approval`: FDA approval / PDUFA / positive trial result
  - `fda-rejection`: CRL / trial fail / safety concern
  - `ma-announcement`: merger / acquisition / tender offer
  - `analyst-upgrade`: analyst upgrade or PT raise
  - `downgrade-short`: analyst downgrade / PT cut (typically short setup)
  - `insider-buy`: insider / 13-D cluster buy
  - `breakout-momentum`: technical breakout w/ volume, no single catalyst
  - `macro-headline`: Fed / CPI / jobs / geopolitical / oil shock
  - `crypto-pump`: crypto-correlated equity move (COIN, MSTR, MARA, etc.)
  - `biotech-catalyst`: biotech catalyst other than FDA (partnership, Phase data)
  - `generic`: fallback only when none of the above fit

## Response
Respond ONLY with valid JSON:
{
  "action": "create_playbook" | "info_only" | "none",
  "conviction": 0-100,
  "thesis": "1-3 sentence rationale grounded in the research",
  "risks": ["list of concrete risks"],
  "playbook": {
    "name": "...",
    "description": "...",
    "priority": 5,
    "templateId": "earnings-beat-smallcap | earnings-miss | fda-approval | fda-rejection | ma-announcement | analyst-upgrade | downgrade-short | insider-buy | breakout-momentum | macro-headline | crypto-pump | biotech-catalyst | generic",
    "conditions": [{"type":"news_keyword","params":{"keywords":["..."]}}],
    "conditionLogic": "all",
    "actions": [{"type":"bracket_entry","market":"alpaca","params":{"symbol":"GLD","qty":"2","entryType":"market","takeProfit":"320","stopLoss":"295","side":"buy"}}],
    "maxExecutionsPerDay": 1,
    "cooldownMs": 3600000,
    "tags": ["..."]
  }
}
If action != "create_playbook", omit the "playbook" field.

019e2b37-e3e4-7110-8ef6-bd6c94060778

Input

Output

Feedbackinference

Inference Parameters

Tool Parameters

Tags

Model Inferences

Feedback
inference