---
name: alphagbm-investment-thesis
description: Record buy rationale and structured sell conditions for stock positions, with automatic monitoring to detect when exit triggers fire.
---

# AlphaGBM Investment Thesis

Turn "I bought this because…" into a tracked, monitored record. Each thesis pairs a prose buy-reason with structured sell conditions so the system can auto-detect when the reasoning no longer holds.

## When to use

- User wants to document *why* they bought a stock
- User wants to set exit triggers (price, PE, fundamental breach)
- User asks which theses are still valid vs triggered
- User asks to update / refine an existing thesis
- User mentions "论据" / "买入理由" / "卖出条件" / "thesis" / "exit trigger"

## Prerequisites

- **API Key**: env `ALPHAGBM_API_KEY` (format `agbm_xxxx…`).
- **Base URL**: default `https://alphagbm.zeabur.app`. Override via `ALPHAGBM_BASE_URL`.
- **Profile required**: A thesis must attach to an existing company profile. If the user hasn't created a profile for the ticker, call `POST /api/research/profiles` first (see `alphagbm-company-profile`).

## API Endpoints

All endpoints require `Authorization: Bearer $ALPHAGBM_API_KEY`.

### 1. List theses

```
GET /api/research/theses?status=active
```

| Query | Values | Description |
|-------|--------|-------------|
| `status` | `active` / `triggered` / `closed` | Optional filter |

**Response:**
```json
{
  "success": true,
  "theses": [
    { "id": 12, "ticker": "NVDA", "buy_thesis": "...", "status": "active", ... }
  ]
}
```

### 2. Get thesis by ticker

```
GET /api/research/theses/<TICKER>
```

Returns the *active* thesis for a ticker. 404 if none exists.

### 3. Create thesis

```
POST /api/research/theses
Content-Type: application/json

{
  "ticker": "NVDA",
  "buy_thesis": "AI capex cycle; data-center GPU moat; FCF > $60B.",
  "sell_conditions": [
    { "type": "price_drop_pct",  "value": 20 },
    { "type": "pe_above",        "value": 60 },
    { "type": "growth_below",    "value": 15 },
    { "type": "thesis_breach",   "value": "cloud capex guidance cut > 20%" }
  ]
}
```

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `ticker` | string | yes | Must match an existing profile |
| `buy_thesis` | string | yes | Free-form prose, recommend 2-4 sentences |
| `sell_conditions` | array | no | Structured triggers (see types below) |

**Common `sell_conditions` types:**
- `price_drop_pct` — drop from purchase/peak %
- `pe_above` / `pb_above` — valuation ceiling
- `growth_below` — revenue/earnings growth threshold
- `thesis_breach` — free-text qualitative trigger (monitored manually)

### 4. Update thesis (by id)

```
PUT /api/research/theses/<THESIS_ID>
Content-Type: application/json

{"buy_thesis": "updated prose", "sell_conditions": [...], "status": "closed"}
```

Partial updates allowed. Note: **uses `thesis_id` (int)**, not ticker — read the id from a prior `list` or `get`.

### 5. Delete thesis (by id)

```
DELETE /api/research/theses/<THESIS_ID>
```

Hard-delete. Also uses numeric id.

## Response schema — full thesis

```
{
  id, ticker,
  buy_thesis,                     // prose
  sell_conditions,                // [{type, value}]
  status,                         // "active" | "triggered" | "closed"
  thesis_score,                   // AI confidence 0-100 (if scored)
  ai_feedback,                    // AI critique of the thesis (markdown)
  triggered_at, trigger_detail,   // populated when status flips
  created_at, updated_at
}
```

## Status lifecycle

```
active ──(sell condition fires)──▶ triggered
   │                                   │
   └────────(user closes)──▶ closed ◀──┘
```

When `status = "triggered"`, `trigger_detail` shows which condition fired. Surface this to the user — it's the whole point of the system.

## Typical Workflow

```
1. User: "I'm buying NVDA because AI capex is still accelerating"
   → (ensure profile exists — see alphagbm-company-profile)
   → POST /api/research/theses with buy_thesis + sell_conditions
   → Confirm: "Saved. Monitoring: price drop > 20%, PE > 60, growth < 15%."

2. User: "What are my active theses?"
   → GET /api/research/theses?status=active
   → Table: ticker · one-line thesis · conditions · score

3. User: "Any theses triggered?"
   → GET /api/research/theses?status=triggered
   → Alert list with trigger_detail explaining why

4. User: "Update my NVDA thesis — exit if PE > 70 instead of 60"
   → GET /api/research/theses/NVDA to find id
   → PUT /api/research/theses/<id> with revised sell_conditions
```

## Output Formatting Tips

When presenting a thesis to the user, highlight:
1. **Ticker + status** (with color/emoji: active=green, triggered=red, closed=gray)
2. **Buy thesis** — first 2 sentences verbatim
3. **Sell conditions** — bulleted, human-phrased ("Exit if price drops 20%")
4. **If triggered** — which trigger fired, lead with that
5. **AI feedback / score** — if present, show as a pull-quote
6. **Age** — "written 3 weeks ago, reviewed 2 days ago"

## Related Skills

- **alphagbm-company-profile** — Prerequisite. A thesis attaches to a profile.
- **alphagbm-health-check** — Surfaces theses that may have drifted from their original premise
- **alphagbm-stock-analysis** — Run a fresh analysis to sanity-check a thesis

---

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