5 new capabilities — research flow from "industry rank" all the way to "business segments"

Researching a stock. What's your pre-open order?

Which sector is strongest today → which sub-segments make up the sector, who's running → pick a name and check institutional ratings → does the print match analyst expectations → which businesses drive the revenue?

These 5 moves — this CLI update fills in each one ✨

This release: 3 new commands + 2 new views / sub-commands.

• 📊 industry-rank — industry gain/loss ranking by market (US/HK/CN/SG) + sector leaders
• 🔍 industry-peers — sector sub-segment tree, full competitive map
• 🎯 institution-rating --views — month-by-month rating trend (buy/hold/sell)
• 💎 financial-report snapshot — AI earnings summary + revenue/EBIT/EPS vs analyst estimates
• 📈 business-segments — revenue broken out by segment, current + historical

MCP ships these in parallel (Tools count now 133). SDK v4.1.0 opens the full set to developers (details at the end).

One overview table below, then 4 worked scenarios.

Full picture of this release

Scenario walkthroughs

1. Pre-open | industry-rank + industry-peers — industry strength + sub-segment tree

Start of the research chain — pre-open, see where strength is sitting.

When to use:

• 9:25 AM pre-open. Which US / HK sector is running today?
• End of earnings season. Which sectors are getting collectively re-rated by analysts?
• Walking into an unfamiliar sector. How many sub-segments, how many names each, YTD up or down?

Commands

longbridge industry-rank --market US # today's US sector gain/loss ranking

longbridge industry-peers BK/US/IN00322 # drill into a sector for sub-segments

(The sector code BK/US/IN00322 is copy-paste from the industry-rank output — every sector has its own code.)

Why it matters: "Which sector is strongest today → which sub-segment inside is driving → who's the leader" — one drill path.

US sector gain/loss ranking + leaders

Drilling into a sector (commercial printing) for sub-segments

2. Sell-side view | institution-rating --views — how analysts shift month by month

You've picked a name from the leader list or a sub-segment. Next question: how have analysts been changing their minds this year?

When to use:

• Day after earnings — did ratings flip in unison?
• A company transitioning from "growth" to "value" — sell-side usually moves first (ratings shift before price)
• Long-term recap — find the key inflection months in the past 2–3 years

A single snapshot of current ratings is noisy. Buy / hold / sell evolution by month shows the actual months when sell-side flipped collectively.

Commands

longbridge institution-rating NVDA.US --views # NVDA monthly rating evolution

Why it matters: Buy column up + Sell column at zero = sell-side converging. The reverse = divergence. Monthly aggregation is steadier than event-day reads — it cuts short-term noise.

3. Post-earnings | financial-report snapshot — 3 metrics vs consensus + AI summary

Sell-side stance checked. Next: how did the print actually land?

When to use:

• US earnings night (post-market 4 PM / after close) — beat or miss, fast call
• Recapping a past quarter against that quarter's consensus
• Comparing several names in the same sector on how close they printed to consensus

You used to wait for sell-side notes or run your own model to call beat-or-miss. Now AI gives you one paragraph on YoY moves and whether it beat; the Forecast vs Actual table lines up revenue / EBIT / EPS against consensus row by row.

Commands

longbridge financial-report snapshot AAPL.US --report qf --year 2024 --period 4 # AAPL FY2024 Q4 earnings snapshot

Why it matters: AI summary (YoY + beat status) + 3-metric beat/miss vs consensus + key financials YoY — all in one screen.

The latest quarter's consensus may not be back-filled yet — pick a historical quarter for the full feature.

4. Segment breakdown | business-segments — which businesses drive the revenue

Numbers done. Last question: where does this revenue / growth actually come from?

Commands

longbridge business-segments NVDA.US # current-period segments

longbridge business-segments NVDA.US --history --report qf # multi-year quarterly segment history

When to use:

• NVDA graphics vs compute & networking mix shift — verify whether the AI transition is actually landing in revenue
• Internet companies — which segment (ads / cloud / gaming / fintech) is growing, which is shrinking
• Concentration risk — is the main segment too dominant, is the company single-business

Why it matters: earnings reports give you total revenue — the real driver hides in segments. --history shows segment mix evolving over years.

$NVIDIA(NVDA.US) current-period segments

$NVIDIA(NVDA.US) quarterly segment history

Also: SDK v4.1.0 ships in parallel

For API developers — this release opens the CLI / MCP capability set to the SDK too:

• 7 new Context types, 66 methods total (Fundamental / Market / Calendar / Portfolio / Alert / DCA / Sharelist)
• QuoteContext gets 4 new methods; ContentContext gets topic-related methods
• Rust SDK supports custom HTTP / WS headers; param types switched to typed enums; currency fields unified to Decimal

SDK docs: https://open.longbridge.com/zh-CN/docs/sdk

🔧 How to install or update

Update: in your terminal, run longbridge update, enter your password. Done.

See what's in this release: longbridge update --release-notes

If Longbridge Skill is installed, the CLI works automatically.

Not installed yet? Quick start:

Tutorial post: [Installation Guide] Step-by-step to install Longbridge Skill + CLI

• Official docs: https://open.longbridge.com/zh-CN/docs/cli
• Mainland users: https://open.longbridge.cn/docs/cli

Sector strength. Sell-side conviction shift. Earnings beat or miss. Segment-level drivers —

The questions you'd ask top to bottom about one stock, you can now run end to end in the terminal.

Comment challenge 🎯: pick a sector you're researching or a single name, and tell me which new command you want first — we'll run it and post the result in the comments.