---
name: portfolio-swarm-review
description: Multi-agent swarm review of kcn's current holdings. Inspired by TauricResearch/TradingAgents framework already in workspace — three-tier analysis (analysts → bull/bear debate → risk debate + judge) with confidence scoring. Use for post-close reviews, holiday/next-session planning, pre-add sizing decisions, and any moment where a single-pass review is not enough. For lighter single-shot work, use portfolio-risk-review.
---

# Portfolio Swarm Review

Multi-agent portfolio review. Structure mirrors the TauricResearch/TradingAgents design — analysts (Tier 1) → researchers (Tier 2) → risk debators + judge (Tier 3). Each tier is distinct in the output; the Judge synthesizes. (The reference repo is no longer cloned locally; the structure is recorded here.)

## Required reads

In this order:
1. `/root/.openclaw/workspace/MEMORY.md`
2. `/root/.openclaw/workspace/portfolio.json`
3. `/root/.openclaw/workspace/memory/current-portfolio-summary.md`
4. `/root/.openclaw/workspace/INVESTMENT_SOP.md`
5. Recent daily memory files when recent trades affect interpretation
6. `/root/.openclaw/workspace/TOOLS.md` for data chain detail

## Fresh data rule

Refresh quotes before producing conclusions:

```bash
python3 /root/.openclaw/workspace/scripts/data/analyze_us_stocks.py    # US 7-route fallback
python3 /root/.openclaw/workspace/scripts/data/analyze_hk_stocks.py    # HK Tencent → stooq → yfinance
```

If a leg is stale, name the exact ticker and limit confidence on conclusions involving it. **00100 only has Tencent** — flag explicitly if that leg fails. KR linkage (07709/07747) is exited; do not run any KR-side fetch.

## Holdings bucketing — read each run, do not hardcode

Pull live set from `portfolio.json` (`shares > 0`) and `current-portfolio-summary.md`. Stable bucket structure; contents drift:

- **US growth / single-name beta** — active US non-leveraged growth names
- **US leverage ETF** — anything `is_leveraged_etf: true`
- **US theme / special situation** — catalyst-driven names
- **HK lower-beta core** — index/sector ETFs (e.g. 03032, 03033)
- **HK single-name** — individual equities (e.g. 00100 AI, 02208 wind)
- **HK leverage ETF** — 2x/3x recipes (e.g. 07226)

## Regime detection (run first)

Before any role analysis, classify current regime — this calibrates everything downstream:

| Regime | Trigger | Implication for sizing |
|---|---|---|
| **Trending up** | Index ADX > 25, MA20 > MA50, RSI 50-70 across book | Momentum-friendly — leveraged ETF holdable, trim only on overheats (RSI > 75) |
| **Trending down** | Index ADX > 25, MA20 < MA50, broad lower lows | Risk-off — leveraged ETF decay accelerates, prefer cash, no add |
| **Range-bound** | ADX < 20, sideways action, RSI mean-reverting around 50 | Mean-reversion plays — T-only, fade extremes |
| **Volatile / regime change** | High variance, conflicting MA stacks, sentiment chaos | Reduce size, widen stops, no convictions until clarity returns |

Index proxies: 纳指 / QQQ for US growth book; ^HSTECH for HK tech-heavy book.

## Tier 1 — Analysts (parallel)

Four analyst roles, run independently. Mirrors `tradingagents/agents/analysts/`.

### Analyst 1 — Position / Market
- For each active holding: price vs cost, PnL $ and %, distance to breakeven
- Technical state: trend, RSI-14, MA20/50 stance, immediate support/resistance
- Classify: core / tactical / weak / leverage-risk
- Output: one-line verdict per ticker + strongest/weakest called out

### Analyst 2 — Fundamentals
- Recent earnings / revenue trend for non-ETF names
- Valuation snapshot (P/E, P/S vs sector and history)
- Balance sheet headlines for special-situation names (cash runway, debt)
- For ETFs: underlying basket health, NAV premium/discount, decay since holding date
- Output: per non-ETF holding — "fair / stretched / cheap"; per ETF — "structurally OK / decay-risk now"

### Analyst 3 — News / Sentiment
- Finnhub news from scripts (`analyze_*_stocks.py` without `--no-news` already pulls 7 days + keyword sentiment)
- For US names: Reddit (r/wallstreetbets + r/stocks JSON, no auth) + Tavily news/X
- For HK names: 雪球 HK 评论区 + 富途社区 (scrapling StealthyFetcher) + Tavily 中文搜索
- 南向资金 当日 net (web search) for HK macro tone
- Output per holding: sentiment score -1 to +1 + 1-2 narratives + divergence vs price call-out

### Analyst 4 — Cross-Market Linkage
- US side: 纳指 / 罗素 / SOX tone; theme threads (stablecoin reg for CRCL, space/defense for RKLB, AI infra threads)
- HK side: 恒科 direction; 南向资金 flow; sector policy (风电 / AI / 监管)
- Inter-market: US tech overnight → HK tech open relationship; note when the link breaks
- Output: supportive / neutral / weak tag per chain, single most important inter-market signal

## Tier 2 — Bull vs Bear Researchers

Mirrors `tradingagents/agents/researchers/`. Run after Tier 1; each researcher reads all four analyst reports and argues a position.

### Bull Researcher
- Compose the strongest "hold and add" case using Tier 1 outputs
- Cite specific analyst findings as evidence (not gut)
- Identify what would have to be true for the position to work out
- Call out asymmetric upside specifically (leverage, catalyst dates, sentiment-vs-fundamentals gaps)

### Bear Researcher
- Compose the strongest "trim and avoid" case
- Cite specific risk findings, decay math, sentiment topping signals
- Identify the worst plausible outcome and what triggers it
- Counter the bull's strongest point directly

The output is a debate snippet (not a checklist), 100-200 words each side.

## Tier 3 — Risk Debate + Judge

Mirrors `tradingagents/agents/risk_mgmt/` + `managers/risk_manager.py`.

### Aggressive Risk Voice
- Argues for upside capture; pushes for full sizing on conviction names
- Quotes bull's strongest points
- Specifically calls out where the conservative voice misses opportunity cost

### Conservative Risk Voice
- Argues for capital preservation; pushes for trim on weak structure
- Quotes bear's strongest points
- Specifically calls out where the aggressive voice underestimates tail risk

### Neutral Voice
- Calls the middle ground — what specifically should size up, what should size down, what stays
- Required: pick a side for each contested holding, no "it depends" outputs

### Judge (Risk Manager)
Final synthesis. Weighs the three risk voices given:
- The user's documented risk preference: **aggressive** (per workspace MEMORY.md), so the aggressive voice gets weight unless its structural counter is strong
- Current regime (from regime detection above)
- Data freshness — any stale leg downgrades confidence

Output buckets per ticker:
- **Hold and watch** — thesis intact, no action
- **Trim on rebound** — thesis weakening, wait for strength
- **T-only** — no overnight conviction, fade extremes
- **Add only on trigger** — explicit trigger (price / MA cross / earnings / policy)
- **Cut** — thesis broken, exit on next acceptable bid (use sparingly)

Each item: ticker + concrete reason + concrete trigger/level if applicable.

## Confidence scoring

End the report with a confidence score per major call, 0-100%:

| Confidence | Calibration |
|---|---|
| 80-100% | All four analysts align, both researchers' strongest cases converge, fresh data, regime clear |
| 60-79% | Most analysts align, one analyst dissents, regime clear |
| 40-59% | Analysts split, regime mixed, or one major data leg stale |
| 20-39% | Conflicting signals, regime change suspected, multiple stale legs |
| < 20% | Don't act on this read; wait for clarity |

## Final output structure

### Header
- Regime: {trending up / trending down / range / volatile}
- Data freshness: timestamp + any stale ticker flagged with ⚠️
- Book summary: total US PnL, total HK PnL, biggest winner/loser

### Tier 1 — Analyst reports
Four sub-sections (Market, Fundamentals, News/Sentiment, Cross-Market). Each terse — tables where data, prose where judgment.

### Tier 2 — Bull vs Bear
Two paragraphs, side by side framing.

### Tier 3 — Risk debate
- Aggressive voice (paragraph)
- Conservative voice (paragraph)
- Neutral voice (paragraph)

### Judge synthesis
Five action buckets with tickers and reasons.

### Confidence calls
Bullet list: "{Action} {Ticker} — confidence XX% — {one-line reason}"

### Next-session plan
Concrete plan: what to watch first at the open, which holdings matter most, price/macro triggers that flip the stance.

## Style rules

- Practical, not academic
- Every claim tied to a real ticker in the current book
- The four analysts' outputs must be DIFFERENT angles, not the same content reformatted
- Bull/Bear must actually disagree on at least one position — if they fully agree, the debate failed and the user should know
- Don't let high-conviction theme hide a bad structure (e.g. "RKLB story is strong" doesn't mean today's RSI 75 is a buy)
- Tables for any 3+ data points
- ⚠️ stale data flagged before any conclusion uses it
- Final plan concise enough to trade from