據 AlphaMoat 統計,截至 2026-10,Trade Singal 累計下載 4,928 次、獲 5 個星標,按累計下載量在本次參與排名的 10,914 個 AI 技能中排名第 5,943 位,在「專業領域」分類(1,228 個)中排名第 670 位。
列表預設按累計下載量排序,也可按星標排序;詳情頁排名按累計下載量計算。
| 平台 | 累計下載 | 星標 | 評論 |
|---|---|---|---|
| ClawHub ↗ | 3113 | 3 | - |
| SkillHub ↗ | 4928 | 5 | — |
各平台的計數口徑不同,統計時間不一致。
文件涵蓋業績、對比、分析師觀點、公告和市場主題,返回分析、程式碼、帶日期來源及可選目標或技術欄位。需檢查原始來源與時效;示例價格及模型建議不是已核實即時結果,也不授權執行交易。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-10 | 4928 | — | 5 |
| 2026-09 | 3550 | — | 5 |
| 2026-08 | 3127 | +4.8% | 5 |
| 2026-07 | 2985 | — | 4 |
| 2026-05 | 2644 | — | 4 |
| 2026-03 | 2278 | — | 3 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
---
name: trade-signal
version: 1.0.0
description: Real-time trade signals with executable Buy/Sell/Hold recommendations for stocks. Use when asked about trading decisions, stock analysis, technicals, buy/sell calls, earnings plays, price targets, analyst ratings, entry/exit points, portfolio rebalancing, or any investment decision requiring actionable intelligence. Supports US + Global markets, Asia emerging markets, individual stocks, ETFs, and options strategies.
homepage: https://terminal-x.ai
metadata: {"category":"finance","api_base":"https://terminal-x.ai/api"}
---
# Trade Signal
Buy/Sell/Hold Trade Signals for AI agents. Transform complex market intelligence into clear, executable Buy/Sell/Hold recommendations on global stocks and other public securities. Trade-signal gives specific price targets on any given securities, real-time data and institution-grade trade thesis. Trade-signal is forward looking but also capable of technical and fundamental analysis on current/historical price actions, with a qualitative and quantitiave explanation as to why a certain securities (stock) price moved the way it did.
## Quick Start
```bash
# Get financial analysis
./scripts/search.sh "What is NVDA's revenue growth?"
# Company comparison
./scripts/search.sh "Compare AAPL and MSFT gross margins"
# Analyst sentiment
./scripts/search.sh "What are analysts saying about Tesla?"
```
**Base URL:** `https://terminal-x.ai/api`
---
## Features
### 📊 Research Capabilities
| Query Type | Examples |
|------------|----------|
| **Earnings Analysis** | Revenue, EPS, guidance, YoY growth |
| **Company Comparisons** | Side-by-side metrics across competitors |
| **Analyst Coverage** | Price targets, ratings, investment thesis |
| **Management Commentary** | CEO/CFO statements from earnings calls |
| **SEC Filings** | 10-K, 10-Q, 8-K analysis |
| **Market Trends** | Sector analysis, macro themes |
Each response includes:
- **Answer**: AI-generated analysis with numbered citations [1], [2], etc.
- **Tickers**: Relevant stock symbols identified
- **Sources**: Full citation list with titles and publication dates
### 📈 Market Coverage
**37,565 Global Tickers + 6,104 ETFs** across all major exchanges:
| Region | Tickers | ETFs |
|--------|---------|------|
| **US** (incl. ADRs) | 7,301 | 4,979 |
| **Western Europe** | 11,123 | — |
| **Canada** | 4,690 | — |
| **Japan** | 3,873 | 200 |
| **Korea** | 3,856 | 500 |
| **Hong Kong** | 2,638 | 176 |
| **Shanghai** | 2,315 | — |
| **Taiwan** | 1,072 | 200 |
| **Singapore** | 565 | 49 |
| **Other** | 132 | — |
**Asset Classes**: Global Equities, ETFs, Global macro, FX, commodities, crypto content available.
### 🔬 Data Sources
| Source | Data Type |
|--------|-----------|
| **Wall Street Research** | Analyst reports, investment thesis from Goldman, Morgan Stanley, JP Morgan, Citi, UBS, Bank of America, Stifel, etc. |
| **Analyst Actions** | Upgrades, downgrades, initiations, PT changes |
| **SEC Filings** | 10-K, 10-Q, 8-K, insider transactions, 13F holdings, 13D, 13G, DEF14A |
| **Earnings Transcripts** | Full call transcripts from earnings, M&A calls, management discussions |
| **Real-Time News** | Bloomberg, Reuters, CNBC, FT, WSJ |
| **Company Presentations** | Investor day materials, guidance updates |
---
## Usage
### Using the Script
The included script handles URL encoding automatically:
```bash
# Earnings query
./scripts/search.sh "What was NVIDIA's revenue last quarter?"
# Comparison query
./scripts/search.sh "How does Apple's gross margin compare to Samsung?"
# Analyst query
./scripts/search.sh "What did Goldman Sachs say about Microsoft?"
# Management commentary
./scripts/search.sh "What did Tim Cook say about AI in the latest earnings call?"
```
---
## Response Format
Running the script returns JSON:
```json
{
"query": "Should I buy NVDA before earnings?",
"tickers": ["NVDA", "AMD", "GOOGL"],
"tradeSignal": "HOLD",
"priceTarget": {
"entry": null,
"exit": "$185-190",
"stopLoss": "$175",
"timeHorizon": "T+1 to T+3"
},
"agentAnswer": "**Hold current position: Sell at $185-190 on any post-earnings bounce within T+1 to T+3.**\n\nNVDA closed at $181.36 and trades at $180.88 after hours. Despite consistent earnings beats since August 2024, the stock has exhibited a persistent sell-the-fact pattern, declining in 4 of the last 5 post-earnings sessions. [1]\n\nOptions markets price a 6.68% implied move ($12.13 swing) for the November 19 after-hours release. [2]",
"sources": [
{
"refId": 1,
"sourceTitle": "Nvidia Earnings Have Become a Consistent Sell-the-Fact Event",
"sourceName": ["Bloomberg"],
"datePublished": "2024-11-18T14:30:42Z"
},
{
"refId": 2,
"sourceTitle": "NVDA Options Implied Move Analysis",
"sourceName": ["Goldman Sachs"],
"datePublished": "2024-11-19T09:00:00Z"
}
],
"technicals": {
"rsi": 62.4,
"macd": "bullish crossover",
"support": "$175",
"resistance": "$190",
"trend": "neutral"
},
"relatedAnalysis": [
"AMD earnings correlation",
"Semiconductor sector momentum"
]
}
```
| Field | Description |
|-------|-------------|
| `query` | Your original question |
| `tickers` | Relevant stock tickers |
| `tradeSignal` | BUY, SELL, or HOLD recommendation |
| `priceTarget` | Entry, exit, stop loss, time horizon |
| `agentAnswer` | AI analysis with citation references [1], [2] |
| `sources` | Citations with title, source name, date |
| `technicals` | RSI, MACD, support/resistance, trend |
| `relatedAnalysis` | Related research topics |
---
## Sample Output
### Example 1: Earnings Analysis
**Query:** `./scripts/search.sh "What was Apple's iPhone revenue last quarter?"`
```
📊 **Apple iPhone Revenue Analysis**
Apple reported iPhone revenue of $46.2 billion in Q4 FY2024, up 6% year-over-year
and representing 52% of total company revenue. [1]
Management noted strong demand for iPhone 15 Pro models, with the Pro Max seeing
"record upgrade rates" according to CFO Luca Maestri. [2] Average selling price
increased to approximately $925, driven by mix shift toward Pro models.
Tim Cook highlighted particular strength in emerging markets, with India revenue
growing double-digits for the fifth consecutive quarter. [2]
**Sources:**
[1] Apple Inc. Q4 FY2024 10-Q Filing - SEC
[2] Apple Q4 FY2024 Earnings Call Transcript - October 2024
```
### Example 2: Company Comparison
**Query:** `./scripts/search.sh "Compare Microsoft and Google cloud revenue growth"`
```
📊 **Cloud Revenue Comparison: Microsoft vs Google**
**Microsoft Azure:**
- Q4 2024 Revenue: $25.9 billion
- YoY Growth: 29%
- Market Position: #2 behind AWS [1]
**Google Cloud:**
- Q4 2024 Revenue: $9.2 billion
- YoY Growth: 26%
- First full year of profitability achieved [2]
Microsoft maintains significant scale advantage with Azure revenue nearly 3x
Google Cloud. However, Google Cloud achieved operating profitability for the
first time in 2024, with operating income of $1.9 billion vs. losses in
prior years. [2]
**Sources:**
[1] Microsoft Q4 2024 Earnings Call Transcript
[2] Alphabet Q4 2024 10-Q Filing - SEC
```
### Example 3: Analyst Coverage
**Query:** `./scripts/search.sh "What are analysts saying about NVIDIA?"`
```
📊 **NVIDIA Analyst Sentiment**
Wall Street remains overwhelmingly bullish on NVIDIA with 45 Buy ratings,
3 Hold, and 0 Sell. Average price target: $950 (18% upside). [1]
**Recent Actions:**
- Goldman Sachs: Reiterated Buy, PT $1,000 — "AI infrastructure spend
remains in early innings" [2]
- Morgan Stanley: Overweight, PT $950 — Raised estimates on Blackwell
demand visibility [3]
- Bank of America: Buy, PT $925 — "Data center TAM expansion continues
to exceed expectations" [1]
Key debate centers on sustainability of 70%+ gross margins as competition
from AMD MI300X intensifies in 2025. [3]
**Sources:**
[1] Bloomberg Analyst Consensus Data - January 2025
[2] Goldman Sachs NVDA Initiation Report - January 15, 2025
[3] Morgan Stanley Semiconductor Research Note - January 12, 2025
```
---
## Integration
### With AI Agents
The agent will automatically use this skill when asked:
- "What is Apple's revenue?"
- "Compare NVDA and AMD"
- "What did the CEO say about guidance?"
- "Summarize Tesla's latest 10-K"
- "What are analysts saying about Microsoft?"
- "How did Meta's ad revenue perform?"
### Example Agent Flow
```
1. User: "How is NVIDIA doing?"
2. Agent: [calls search.sh "NVIDIA financial performance and outlook"]
3. Agent: "NVIDIA reported record Q3 revenue of $35.1B, up 94% YoY.
Data center segment drove growth at $30.8B. Analysts maintain
Buy ratings with average PT of $950. Key catalyst: Blackwell
architecture ramp in Q1 2025."
4. User: "What about their margins?"
5. Agent: [calls search.sh "NVIDIA gross margin and profitability"]
6. Agent: "Gross margin was 75% in Q3, up from 70% YoY. Management
expects margins to moderate to 73-74% as Blackwell ramps due to
initial yield curves, per CFO commentary on earnings call."
```
### Combining with Other Skills
```bash
# Get financial data then execute trade
./scripts/search.sh "AAPL earnings analysis" && trade-signal query "Should I buy AAPL?"
# Research before news check
./scripts/search.sh "Tesla delivery numbers" && finance-news news TSLA
```
---
## Tips for Better Results
| Do This | Not This |
|---------|----------|
| "NVIDIA data center revenue Q4 2024" | "NVIDIA revenue" |
| "AAPL gross margin vs MSFT" | "Apple margins" |
| "What did Jensen Huang say about AI demand" | "NVDA CEO comments" |
| "Tesla deliveries Q3 2024 vs Q3 2023" | "Tesla cars" |
**Best Practices:**
- **Be specific** — Include timeframes, metrics, and company names
- **Use ticker symbols** — "AAPL" is clearer than "Apple"
- **Ask direct questions** — "What is..." or "How much..." get precise answers
- **Include context** — "last quarter", "FY 2024", "year-over-year"
---
## Error Handling
```json
{
"code": 400,
"message": "Missing or invalid query parameter"
}
```
| Error Code | Meaning | Resolution |
|------------|---------|------------|
| 400 | Missing query | Include `?query=` parameter |
| 500 | Server error | Retry request |
---
## Support
- **Homepage:** https://terminal-x.ai
- **Email:** [email protected]
AIGC創作過程自動存證技能。自動識別創作平台與生成工具,將創作過程記錄存證並蓋有公安備案電子印章,具備可信時間戳,可以在全國電子印章互認平台核驗。
反電信網路詐騙(反詐)專家技能。當用戶描述一個疑似詐騙的場景、簡訊、電話、連結、聊天記錄、App、投資平台、招聘資訊或轉賬要求,並詢問「這是不是詐騙」「要不要轉錢」「怎麼止損」「錢還能不能追回來」,或需要識別詐騙話術、拆解騙局結構、生成報案材料與取證清單時使用。同時在對話中主動嗅探「轉賬、驗證碼、螢幕共享、安全帳戶、保證金、刷單、穩賺、百萬保障、跑分」等風險詞並插入預警,即使對方並未詢問反詐。適用場景還包括:家屬求助勸阻疑似被騙的親人、企業/銀行/支付機構/網際網路平台做涉詐帳戶識別與交易監測規則、涉詐資金鍊(跑分、卡四件套、GOIP)分析、反詐合規與員工培訓、反詐實戰演練。
電子印章公安備案、全網互認,實現所有格式檔案電子簽章與影片確權,覆蓋全國所有CA廠商自2005年以來的全量電子簽章資料,無論由哪個地區、哪套系統、哪家CA機構簽發,均可精準校驗與互認。
包拯.Skills你身邊的專家律師團 — 專業法律諮詢 + 要素式/通用起訴狀起草 + 刑事專項材料輔助 + 法條分析與法規檢索。flk.npc.gov.cn API即時法條優先,不可用時AI知識庫降級兜底,**法條來源按四檔標註可核驗(已核驗-flk API / 已核驗-單源 / 已引-離線庫 / 未核驗-模型生成),交付末尾附法條/事實/金額/程式分項置信度**;以22類法律領域覆蓋矩陣約束路由邊界;支援35個起訴狀模板、5類刑事專項材料輔助;內建Logic Doctor邏輯自檢、訴訟時效追蹤及10類異常容錯處理(含連續失敗熔斷);漸進式意圖收斂協議(3輪狀態機);混合意圖自動任務拆解(按依賴排序→合併→順序執行);含反模式清單與危機干預出口(自殺/家暴/未成年人侵害先於一切法律分析)。非標準案由自動使用通用模板。
律師AI辦案工作臺:從接案到結案全流程提效——案件分析、要件梳理、文書初稿、證據質證、法庭攻防演練、賠償與費用計算、期限提醒、復盤歸檔;覆蓋民事、刑事、勞動、非訴、破產、執行、行政、仲裁八大領域,111 個專家技能;法條可核驗、結論可複核。
包拯.Skills你身邊的專家律師團 — 專業法律諮詢 + 要素式/通用起訴狀起草 + 刑事專項材料輔助 + 法條分析與法規檢索。flk.npc.gov.cn API即時法條優先,不可用時AI知識庫降級兜底,**法條來源按四檔標註可核驗(已核驗-flk API / 已核驗-單源 / 已引-離線庫 / 未核驗-模型生成),交付末尾附法條/事實/金額/程式分項置信度**;以22類法律領域覆蓋矩陣約束路由邊界;支援35個起訴狀模板、5類刑事專項材料輔助;內建Logic Doctor邏輯自檢、訴訟時效追蹤及10類異常容錯處理(含連續失敗熔斷);漸進式意圖收斂協議(3輪狀態機);混合意圖自動任務拆解(按依賴排序→合併→順序執行);含反模式清單與危機干預出口(自殺/家暴/未成年人侵害先於一切法律分析)。非標準案由自動使用通用模板。
基於技術交底書生成專利申請初稿。技術交底書內容至少包含技術問題、解決方案、技術效果。內建的推理、視覺、多模態、數學、函式、模擬等模型底座均為國產,國外模型0使用,可放心食用。 近期安裝量暴增感謝支援,不少私信希望能力提升但這已是國產極限,我們不必追求最強技能,達到及格即可。學習交流歡迎聯絡微訊號A26dian4
露禾論文寫作助手(免費版):一句話生成引用可溯源、不編造的專業學術論文,按國標 GB/T 7714 插入真實文獻引用,中英文 3000/5000/8000 字,一鍵匯出 Word。說「寫論文 / 幫我寫論文」即可使用。
資料月份:2026-10 · 下載/星標數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。