Alphagbm Company Profile

AlphaGBM Company Profile

Build and manage company research profiles in a user's private knowledge base. Each profile captures fundamentals (PE/PB), 8-year valuation bands, financial red flags, and recent events — auto-refreshed on a schedule.

When to use

• User wants to track a company in their personal research workspace
• User asks to list / view / delete saved companies
• User asks for PE or PB historical band of a ticker
• User asks to refresh a stale profile
• User mentions "知识库" / "投研档案" / "research brain" / "knowledge base"

Prerequisites

• API Key: stored in env ALPHAGBM_API_KEY (format agbm_xxxx…).
• Base URL: default https://alphagbm.zeabur.app. Override with env ALPHAGBM_BASE_URL.
• If the user has no key, direct them to register at and create one at /api-keys.
• Tier requirement: Free tier = 1 profile, Plus = 10, Pro = 50. Create endpoint returns 403 with upgrade_required: true when the cap is hit.

API Endpoints

All endpoints require Authorization: Bearer $ALPHAGBM_API_KEY.

1. List profiles

GET /api/research/profiles?page=1&per_page=20

Response:

{
  "success": true,
  "profiles": [{ "ticker": "AAPL", "company_name": "...", "current_price": 261.0, ... }],
  "total": 3,
  "page": 1,
  "per_page": 20
}

2. Get profile detail (includes thesis if one exists)

GET /api/research/profiles/

Returns the full profile + an embedded thesis field (null if no thesis yet). See Response schema below for field list. Returns 404 if the ticker isn't in the user's knowledge base.

3. Create profile

POST /api/research/profiles
Content-Type: application/json

{"ticker": "AAPL"}

Behavior: Pulls fundamentals via the data provider, computes red flags and event radar, persists the profile. If a profile already exists for this user+ticker, it's updated in place (idempotent).

Tier limit response (403):

{
  "success": false,
  "error": "Profile limit reached. Upgrade to Plus for 10 profiles.",
  "current": 1,
  "max": 1,
  "upgrade_required": true
}

4. Delete (archive) profile

DELETE /api/research/profiles/

Soft-deletes by flipping status to archived. Returns 404 if not found.

5. Refresh profile data

POST /api/research/profiles//refresh

Pulls fresh market data, recomputes red flags and events. Use when the user says "refresh my profile" or the last_updated_at is stale (> 7d old).

6. PE/PB Band data (cached 24h)

GET /api/research/profiles//band

Returns 8-year PE/PB history for building the band chart. Can be called without the ticker being in the user's knowledge base — it's a read-only market data endpoint.

Response:

{
  "success": true,
  "ticker": "AAPL",
  "pe_history": [{"date": "2017-04", "pe": 16.2}, ...],
  "pb_history": [...],
  "current_pe_percentile": 0.82,
  "current_pb_percentile": 0.75
}

Response schema — full profile

{
  id, ticker, company_name, market,          // market = US | HK | CN
  current_price, pe_ratio, pb_ratio,
  pe_band_data,                              // 8yr history, same shape as /band endpoint
  financial_red_flags,                       // [{rule_id, severity: "high|med|low", message}]
  event_radar,                               // [{event_type, timestamp, headline}]
  ai_profile_summary,                        // markdown, ~500 chars
  status,                                    // "active" | "archived"
  last_viewed_at, last_updated_at, created_at
}

Typical Workflow

1. User: "Add NVDA to my research brain"
   → POST /api/research/profiles {"ticker": "NVDA"}
   → Present: "Added NVDA. Current PE 45, 2 red flags, PE at 85th percentile of 8yr range."

2. User: "What's in my knowledge base?"
   → GET /api/research/profiles
   → Present table: ticker · company · PE · last_updated · red flag count

3. User: "Show me my AAPL profile"
   → GET /api/research/profiles/AAPL
   → Present: summary, PE/PB bands, red flags list, event radar, linked thesis (if any)

4. User: "Refresh my TSLA profile"
   → POST /api/research/profiles/TSLA/refresh

Tier Limits

When a create hits the limit, the API returns upgrade_required: true. Surface this to the user with a prompt to upgrade at /pricing.

Output Formatting Tips

When presenting a profile to the user, highlight:

1. Ticker + company name and market flag (US / HK / CN)
2. Current price + PE / PB with percentile context ("PE 32, 85th percentile of 8yr range → rich")
3. Red flags — group by severity, show top 3
4. Event radar — most recent 3-5 events with dates
5. Linked thesis — if present, one-line buy reason + exit trigger summary
6. Staleness — if last_updated_at > 7d old, suggest a refresh

Related Skills

• alphagbm-investment-thesis — Attach buy thesis + exit triggers to a profile
• alphagbm-health-check — Detect stale / drifted profiles across the user's workspace
• alphagbm-stock-analysis — One-off deep analysis (not persisted to the knowledge base)
• alphagbm-theme-research — Group profiles into themes (AI infra, HK dividend, etc.)

---

Powered by AlphaGBM — Real-data options & research intelligence for traders and AI agents. 10K+ users.