// Generate QuantMind weekly market reports. Use when the user asks to create a new weekly market report, update report data, or work on the market summary. Triggers on phrases like "weekly report", "market report", "周报", "market summary", or when working in the weekly market summary project.
| name | weekly-market-report |
| description | Generate QuantMind weekly market reports. Use when the user asks to create a new weekly market report, update report data, or work on the market summary. Triggers on phrases like "weekly report", "market report", "周报", "market summary", or when working in the weekly market summary project. |
| version | 1.5.0 |
| last_updated | "2026-02-01T00:00:00.000Z" |
Generate bilingual (Chinese/English) weekly market reports covering US indices, sectors, stocks, crypto, and global markets.
Skill Version: 1.5.0 | Last Updated: 2026-02-01 | Project:
/Users/tim/quantmind/weekly market summary
| Section | Description |
|---|---|
| Quick Start | Decision tree for common tasks |
| Full Workflow | Complete 7-step process |
| Data Validation | NEW: Real-time data freshness validation |
| Example Walkthrough | Real scenario demonstration |
| Headline Patterns | 5 headline templates |
| Narrative Guidelines | Writing patterns for all sections |
| Strategy Templates | Position & recommendation patterns |
| Economic Calendar | Events and calendar format |
| US Market Holidays | 2026 market closures |
| Illustrations | Visual asset creation |
| External Analysis | Integrating video/research insights |
| Quality Checklist | Pre-publish verification |
| Troubleshooting | Common issues and fixes |
| Project Structure | File organization |
| CLI Reference | Command cheat sheet |
| Jinja2 Reference | Template syntax |
| Ticker Reference | Chinese name lookups |
| Search/Replace | Regex patterns for updates |
What do you need to do?
│
├─► Create NEW report for this week?
│ └─► Go to [Full Workflow](#full-workflow)
│
├─► UPDATE existing report narrative?
│ └─► Go to [Step 4: Update Narrative](#step-4-update-narrative-sections)
│
├─► ADD external analysis (video insights)?
│ └─► Go to [Adding External Analysis](#adding-external-analysis)
│
├─► Generate ILLUSTRATIONS?
│ └─► Go to [Illustration Generation](#illustration-generation)
│
├─► FIX data issues?
│ └─► Go to [Troubleshooting](#troubleshooting)
│
└─► Just VERIFY data?
└─► Run: `python run_weekly_report.py YYYY-MM-DD --verify`
Before starting, confirm:
automation/config.py"/Users/tim/quantmind/weekly market summary/venv"┌─────────────────────────────────────────────────────────────────┐
│ 1. FETCH DATA → 2. VERIFY → 2.5 VALIDATE (NEW!) → │
│ │
│ 3. COPY TEMPLATE → 4. UPDATE NARRATIVE → 5. GENERATE HTML │
│ │
│ → 6. EXPORT PDF → (Optional) 7. GENERATE ILLUSTRATIONS │
└─────────────────────────────────────────────────────────────────┘
NEW in v1.5.0: Step 2.5 validates data freshness against real-time sources (crypto via CoinGecko, stocks via Yahoo Finance). Run before publishing!
When: Friday after 4PM ET market close
Commands:
cd "/Users/tim/quantmind/weekly market summary"
source venv/bin/activate
cd automation
python run_weekly_report.py YYYY-MM-DD # e.g., 2026-01-24
Output: market_data_jan24.json (in project root)
What gets fetched:
| Category | Tickers | Count |
|---|---|---|
| Indices | SPY, QQQ, DIA, IWM | 4 |
| Sectors | XLK, XLV, XLF, XLE, XLI, XLP, XLY, XLU, XLC, XLB, XLRE + IWM (Small Cap) | 12 |
| Stocks | NVDA, AAPL, MSFT, GOOGL, META, AMZN, TSLA, LLY, AMD, MU | 10 |
| Crypto | BTC, ETH, SOL | 3 |
| Global | FXI, EWH, EWU, EWJ, EWG | 5 |
Command:
python run_weekly_report.py YYYY-MM-DD --verify
Verification Checklist:
If verification fails: See Troubleshooting
Purpose: Ensure data is current by comparing against real-time sources.
Commands:
cd "/Users/tim/quantmind/weekly market summary/automation"
# Validate all sections against real-time sources
python validate_data.py ../market_data_jan31.json
# Validate and auto-fix stale prices
python validate_data.py ../market_data_jan31.json --auto-fix
# Validate specific section only
python validate_data.py ../market_data_jan31.json --section crypto
python validate_data.py ../market_data_jan31.json --section stocks
python validate_data.py ../market_data_jan31.json --section indices
# Verbose output with all fetched prices
python validate_data.py ../market_data_jan31.json --verbose
What gets validated:
| Section | Data Source | Threshold |
|---|---|---|
| Crypto (BTC, ETH, SOL) | CoinGecko API | >3% diff triggers alert |
| Indices (SPY, QQQ, DIA, IWM) | Yahoo Finance | >1% diff triggers alert |
| Stocks (Mag7 + tech) | Yahoo Finance | >2% diff triggers alert |
| Sectors | Sanity check | >15% weekly return is extreme |
| Global Markets | Sanity check | >10% weekly return is extreme |
When to run:
Example output:
============================================================
QUANTMIND COMPREHENSIVE DATA VALIDATION
File: market_data_jan31.json
Section: all
============================================================
📅 Checking date freshness...
✅ Report date OK (2026-01-31, 1 days ago)
₿ Validating CRYPTO prices (CoinGecko)...
⚠️ Discrepancies found:
- BTC: JSON $84,121 vs Real $78,243 (7.5% diff)
- ETH: JSON $2,702 vs Real $2,370 (14.0% diff)
📊 Validating INDICES prices (Yahoo Finance)...
✅ Index prices are up to date
💹 Validating STOCK prices (Yahoo Finance)...
✅ Stock prices are up to date
🔧 Auto-fixing crypto prices...
Updated BTC: $84,121 -> $78,243
Updated ETH: $2,702 -> $2,370
✅ Updated market_data_jan31.json
CRITICAL: After copying template, always run
validate_report.pyto find stale content!
Commands:
cd "/Users/tim/quantmind/weekly market summary"
# Copy previous template
cp report_generator_jan24.py report_generator_jan31.py
# IMMEDIATELY validate against JSON to find stale content
cd automation
python validate_report.py ../report_generator_jan31.py ../market_data_jan31.json
What gets validated:
| Issue Type | Description | Example |
|---|---|---|
| Stale dates | Dates from previous weeks | "1月17日" when report is 1月31日 |
| Wrong direction | Sign mismatch (+/-) | Report says "+3%" but JSON is -7% |
| Stale prices | Price references don't match | "SPY $698" when JSON has $692 |
| Wrong leaders | Wrong sector as leader | "XLB领涨" when XLC is top |
| Stale percentages | Values differ significantly | "+8%" when JSON shows +2% |
Example output showing issues:
📊 Validating PERCENTAGES...
⚠️ Found 238 percentage issue(s):
- Line 3: MSFT WRONG DIRECTION! Report says +3.00% but JSON is -7.53%
- Line 210: AMD +0.00% in report vs -7.80% in JSON
- Line 211: IWM WRONG DIRECTION! Report says +4.00% but JSON is -2.04%
🏢 Validating SECTOR rankings...
⚠️ Found 20 sector issue(s):
- Line 214: 'XLB' mentioned as leader, but XLC is actually top (+2.40%)
Commands:
cd "/Users/tim/quantmind/weekly market summary"
# Find most recent template
ls -la report_generator_*.py | tail -1
# Copy it (adjust filenames)
cp report_generator_jan17.py report_generator_jan24.py
Important: Always use the most recent generator as your template - it has the latest styling and section structure.
Edit the new report_generator_janXX.py. This is the most critical step.
Required Updates Checklist:
| Priority | Section | Location | What to Update |
|---|---|---|---|
| HIGH | Report dates | Top of class | report_date, week range strings |
| HIGH | Headline theme | <h3>🚀 ... | Main market story (see Headline Patterns) |
| HIGH | Market summary | market-summary div | 4 key bullet points |
| MED | Sector analysis | Section 2 | Leaders/laggards commentary |
| MED | Stock analysis | Section 3 | Individual stock narratives |
| MED | Crypto outlook | Section 5 | BTC/ETH/SOL commentary |
| MED | Strategy section | Section 7 | Current recommendations (see Strategy Templates) |
| HIGH | Next week preview | Section 8 | Upcoming events (see Economic Calendar) |
| HIGH | Roadmap table | "完整操作路线图" | Current position, targets |
| MED | Core summary | "核心观点总结" | Final paragraph |
Date Format Examples:
2026年1月24日1月19日-1月24日2026-01-24Commands:
cd "/Users/tim/quantmind/weekly market summary"
source venv/bin/activate
python report_generator_jan24.py
Output: quantmind-weekly-report-jan-24-2026.html
Post-Generation Check:
QuantMind 本周市场周报 - 2026年1月24日.pdfPDF Export Settings (Chrome):
Common PDF Issues:
Scenario: Creating the Jan 24, 2026 report after market close.
cd "/Users/tim/quantmind/weekly market summary"
source venv/bin/activate
cd automation
python run_weekly_report.py 2026-01-24
Output shows:
SPY $698.50 Week: +0.99% YTD: +2.44%
QQQ $628.00 Week: +1.08% YTD: +2.23%
...
✅ Data fetched and verified successfully!
Looking at the data, identify:
cp report_generator_jan17.py report_generator_jan24.py
Key updates to make:
1月17日 → 1月24日1月12日-1月17日 → 1月19日-1月24日🚀 SPY逼近$700大关：科技股领涨，牛市延续python report_generator_jan24.py
open quantmind-weekly-report-jan-24-2026.html
Check:
QuantMind 本周市场周报 - 2026年1月24日.pdfThe headline (<h3>🚀 ...) should capture the week's dominant theme. Choose from these patterns:
When one stock significantly outperforms/underperforms:
AMD反转狂飙+15.24%，防御板块走强，加密货币回暖
[STOCK]反转狂飙+X.XX%，[secondary theme]，[tertiary theme]
When small vs large cap divergence is significant:
小盘股狂飙：IWM领涨+4.18%，资金轮动加速
风格轮动：[IWM/QQQ] +X.XX%领涨，[context]
When a sector dominates:
科技板块回归：XLK +3.5%引领反弹
[Sector]领涨+X.XX%：[brief catalyst]
When broad market moves uniformly:
全线上涨：SPY突破$700大关，牛市继续
全线回调：避险情绪升温，等待CPI指引
When no clear trend:
多空博弈：指数窄幅震荡，板块分化加剧
震荡整理：SPY横盘，资金观望下周CPI
Always include these 4 bullet points:
<ul>
<li><strong>大盘走势</strong>：SPY本周+X.XX%，收于$XXX，[context - trend continuation/reversal/consolidation]</li>
<li><strong>风格轮动</strong>：[Compare IWM vs QQQ - which style is leading and why]</li>
<li><strong>板块分化</strong>：[Top sector] +X.XX%领涨，[Bottom sector] -X.XX%垫底，[brief reason]</li>
<li><strong>个股亮点</strong>：[Notable mover] +X.XX%[reason]，[secondary mover if significant]</li>
</ul>
Positive performance (+3% or more):
<div style="background: #e8f5e9;">
<strong>✅ [TICKER] +X.XX%</strong>：[catalyst]，[technical note]
</div>
Example catalysts: 财报超预期, AI需求强劲, 产品发布利好, 分析师上调评级
Negative performance (-3% or more):
<div style="background: #ffebee;">
<strong>❌ [TICKER] -X.XX%</strong>：[headwind]，[technical concern]
</div>
Example headwinds: 指引不及预期, 竞争加剧, 估值压力, 监管担忧
Neutral/Mixed (-3% to +3%):
<div style="background: #fff3e0;">
<strong>⚖️ [TICKER] +/-X.XX%</strong>：[context for consolidation]
</div>
Top performers:
[Sector]板块本周+X.XX%领涨，主要受益于[catalyst]。
Bottom performers:
[Sector]板块-X.XX%垫底，压力来自[headwind]。
比特币本周[上涨/下跌]X.XX%至$XX,XXX，[support/resistance level context]。
以太坊[跟随/分化]，+/-X.XX%，[ETH-specific catalyst if any]。
Solana [performance]，生态活跃度[observation]。
全球市场方面，[top performer region]表现最强，[ETF ticker] +X.XX%，受益于[catalyst]。
[bottom performer region]承压，[ETF ticker] -X.XX%，主要受[headwind]影响。
整体来看，[overall observation about global risk appetite/correlation with US markets]。
Region-specific catalysts:
<p style="margin-top: 15px; padding: 12px; background: rgba(25, 118, 210, 0.1); border-radius: 5px; border-left: 4px solid #1976d2;">
<strong style="color: #1565c0;">⚠️ 投资策略总结</strong>：<strong>[主策略]</strong>——[详细说明]。建议[具体操作建议]。<strong>[关注重点]</strong>，[时机建议]。
</p>
Example strategies:
<p style="margin-top: 15px;"><strong>🎯 仓位建议（[时间点]）：</strong></p>
<ul>
<li><strong>XX-XX% 股票</strong>：[市场状态说明]
<ul style="margin-top: 5px; font-size: 13px;">
<li>科技股XX%：[具体建议]</li>
<li>防御板块XX%：[具体建议]</li>
</ul>
</li>
<li><strong>XX-XX% 现金</strong>：[现金策略]</li>
<li><strong>XX-XX% 加密货币</strong>：[加密策略]</li>
</ul>
Position guidance by market condition:
| Market State | Stock % | Cash % | Crypto % |
|---|---|---|---|
| Strong Bull | 70-80% | 10-15% | 10-15% |
| Mild Bull | 60-70% | 20-25% | 10-15% |
| Neutral/Uncertain | 50-60% | 30-35% | 10-15% |
| Defensive | 40-50% | 40-45% | 10-15% |
| Bear Market | 30-40% | 50-55% | 5-10% |
<p style="margin-top: 20px; padding: 15px; background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%); border-radius: 8px; border-left: 4px solid #1976d2;">
<strong>💎 核心观点总结</strong>：本周SPY $XXX（+X.XX%），[周度总结一句话]。[关键观察点]。[展望下周/未来]。<strong>[最终建议]</strong>，[具体行动指引]。
</p>
Check these sources for upcoming market-moving events:
| Event | Typical Day | Market Impact |
|---|---|---|
| CPI | ~10th-15th | HIGH - inflation data |
| PPI | Day after CPI | MED - producer prices |
| FOMC Decision | 8 times/year | HIGH - rate decisions |
| Jobs Report | First Friday | HIGH - employment |
| Retail Sales | Mid-month | MED - consumer spending |
| PCE | End of month | HIGH - Fed's preferred inflation |
<h2>八、下周展望与关键事件</h2>
<ul>
<li><strong>周一（1/20）</strong>：[Event or "马丁·路德·金纪念日，美股休市"]</li>
<li><strong>周二（1/21）</strong>：[Event]</li>
<li><strong>周三（1/22）</strong>：[Event]</li>
<li><strong>周四（1/23）</strong>：[Event or earnings: NFLX, etc.]</li>
<li><strong>周五（1/24）</strong>：[Event]</li>
</ul>
| Date | Holiday | Market Status |
|---|---|---|
| Jan 1 (Thu) | New Year's Day | Closed |
| Jan 19 (Mon) | MLK Day | Closed |
| Feb 16 (Mon) | Presidents' Day | Closed |
| Apr 3 (Fri) | Good Friday | Closed |
| May 25 (Mon) | Memorial Day | Closed |
| Jul 3 (Fri) | Independence Day (observed) | Closed |
| Sep 7 (Mon) | Labor Day | Closed |
| Nov 26 (Thu) | Thanksgiving | Closed |
| Nov 27 (Fri) | Day after Thanksgiving | Early close 1PM |
| Dec 25 (Fri) | Christmas | Closed |
Note: When holidays fall on weekends, markets close on adjacent Friday/Monday.
Create illustrations for key report sections. Store prompts in:
quantmind-weekly-report-jan-XX-2026/illustrations/prompts/
illustration-market-overview.mdillustration-sector-rotation.mdillustration-[theme].md (e.g., semiconductor-reversal)illustration-mag7-outlook.mdillustration-crypto-recovery.mdillustration-global-markets.mdillustration-next-week-outlook.md插图主题: [Theme in Chinese]
风格: elegant (精致优雅) / modern (现代简约) / warm (温暖活力)
视觉构图:
- 主视觉: [Central element description]
- 左侧区域: [Left side elements]
- 右侧区域: [Right side elements]
- 背景: [Background treatment]
- 整体布局: [Layout notes]
配色方案:
- 主色: [Primary color with hex]
- 背景: [Background color with hex]
- 强调色: [Accent colors with hex]
文字内容:
- 中央: "[Main text]"
- 左侧小标: "[Left label]"
- 右侧小标: "[Right label]"
风格要点:
- [Style note 1]
- [Style note 2]
- [Style note 3]
Elegant (精致优雅):
#E8A598#F5F0E6#C9A962, Teal #5B8A8AModern (现代简约):
#1976d2#f5f7fa#ff9800, Green #4caf50Warm (温暖活力):
#c62828#fafafa#ffc107, Deep teal #00796bWhen user provides insights from videos or external research:
Template for new analysis section:
<div style="background: rgba(255, 255, 255, 0.1); padding: 15px; margin: 15px 0; border-radius: 6px; border: 2px solid rgba(255, 152, 0, 0.5);">
<h4 style="color: #ffeb3b; margin-top: 0;">📊 [SECTION TITLE]</h4>
<ul>
<li><strong>[Point 1]</strong>：[Details]</li>
<li><strong>[Point 2]</strong>：[Details]</li>
</ul>
</div>
Stock Rating Table:
<table class="data-table" style="font-size: 13px;">
<tr style="background: #e8f5e9;"><td>✅ GOOGL</td><td>看多 - 技术面强势</td></tr>
<tr style="background: #fff3e0;"><td>⚖️ NVDA</td><td>谨慎 - 头肩顶风险</td></tr>
<tr style="background: #ffcdd2;"><td>❌ TSLA</td><td>看空 - 预期-10%</td></tr>
</table>
Color Conventions:
| Color | Meaning | Background Code |
|---|---|---|
| Green | Bullish/Positive | #e8f5e9 |
| Red | Bearish/Negative | #ffebee or #ffcdd2 |
| Orange | Neutral/Caution | #fff3e0 |
| Blue | Current/Highlight | #e3f2fd |
Run through this checklist before finalizing the report:
Problem: Zero values or missing tickers
# Re-run fetch for specific date
python run_weekly_report.py 2026-01-24
# If still failing, check API key
cat automation/.env
Problem: API rate limit errors
Problem: Wrong week dates in JSON
market_data_janXX.jsonweek_start, week_end, report_date fieldsProblem: Stale dates in narrative Search and replace these patterns:
1月5日-1月10日 → 1月19日-1月24日2026年1月17日 → 2026年1月24日Problem: HTML generation errors
# Check for Python syntax errors
python -m py_compile report_generator_jan24.py
# Check Jinja2 template syntax
python -c "from jinja2 import Template; exec(open('report_generator_jan24.py').read())"
The roadmap table at "完整操作路线图" requires special attention:
<tr style="background: #e3f2fd; border-left: 3px solid #1976d2;">
<td><strong>🔵 当前：2026年1月24日</strong></td>
<td>[Current market phase]</td>
<td>SPY $XXX，[pattern]</td>
<td><strong>XX-XX%</strong></td>
<td>[Strategy]</td>
</tr>
weekly market summary/
├── automation/
│ ├── config.py # Ticker definitions, API config
│ ├── data_fetcher.py # Polygon API client
│ ├── run_weekly_report.py # Main CLI tool
│ └── .env # API keys (not committed)
├── market_data_janXX.json # Current week's data
├── report_generator_janXX.py # Current week's template
├── quantmind-weekly-report-*.html # Generated reports
├── quantmind-weekly-report-jan-XX-2026/
│ └── illustrations/
│ └── prompts/ # Illustration generation prompts
├── archive/ # Old reports and data
└── venv/ # Python virtual environment
# Fetch data for specific date
python run_weekly_report.py 2026-01-24
# Verify existing data
python run_weekly_report.py 2026-01-24 --verify
# Fetch only (no HTML generation prompt)
python run_weekly_report.py 2026-01-24 --fetch-only
# List existing data files
python run_weekly_report.py --list
<!-- Report metadata -->
{{ report_date }} <!-- 2026年1月24日 -->
{{ week_start }} - {{ week_end }}
<!-- Looping through indices -->
{% for idx in indices %}
{{ idx.ticker }} <!-- SPY -->
{{ idx.name }} <!-- 标普500 ETF -->
${{ "%.2f"|format(idx.close) }} <!-- $695.00 -->
{{ '+' if idx.weekly_change > 0 else '' }}{{ idx.weekly_change }}%
{% endfor %}
<!-- Conditional styling -->
<td class="{{ 'positive' if item.weekly_change > 0 else 'negative' }}">
<!-- Number formatting -->
{{ "%.2f"|format(value) }} <!-- 2 decimal places -->
{{ "{:,}".format(value|int) }} <!-- Thousands separator -->
| Data | Template Variable | Fields |
|---|---|---|
| Indices | indices | ticker, name, close, weekly_change, ytd_change, week_high, week_low |
| Sectors | sectors | ticker, sector, weekly_return, monthly_return, ytd_return |
| Stocks | stocks or mag7 | ticker, name, close, weekly_change, ytd_change |
| Crypto | crypto | ticker, name, close, weekly_change, week_high, week_low |
| Global | global_markets | region, index, weekly_return, ytd_return |
| Ticker | Chinese Name | English Name |
|---|---|---|
| SPY | 标普500 ETF | S&P 500 ETF |
| QQQ | 纳指100 ETF | Nasdaq 100 ETF |
| DIA | 道指 ETF | Dow Jones ETF |
| IWM | 罗素2000 ETF | Russell 2000 ETF |
| Ticker | Chinese Name | English Name | Type |
|---|---|---|---|
| XLK | 信息技术 | Technology | Cyclical |
| XLV | 医疗保健 | Healthcare | Defensive |
| XLF | 金融 | Financials | Cyclical |
| XLE | 能源 | Energy | Cyclical |
| XLI | 工业 | Industrials | Cyclical |
| XLP | 必需消费 | Consumer Staples | Defensive |
| XLY | 可选消费 | Consumer Discretionary | Cyclical |
| XLU | 公用事业 | Utilities | Defensive |
| XLC | 通讯服务 | Communication Services | Cyclical |
| XLB | 材料 | Materials | Cyclical |
| XLRE | 房地产 | Real Estate | Interest-sensitive |
Sector Classifications:
| Ticker | Chinese Name | Sector |
|---|---|---|
| NVDA | 英伟达 | AI/Semiconductors |
| AAPL | 苹果 | Consumer Tech |
| MSFT | 微软 | Enterprise Tech |
| GOOGL | 谷歌 | Search/Cloud |
| META | Meta | Social Media |
| AMZN | 亚马逊 | E-commerce/Cloud |
| TSLA | 特斯拉 | EV/Energy |
| LLY | 礼来 | Pharma (GLP-1) |
| AMD | AMD | Semiconductors |
| MU | 美光科技 | Memory |
| Ticker | Chinese Name |
|---|---|
| BTC | 比特币 |
| ETH | 以太坊 |
| SOL | Solana |
| Ticker | Chinese Name | Region |
|---|---|---|
| FXI | 中国大盘ETF | China |
| EWH | 香港ETF | Hong Kong |
| EWJ | 日本ETF | Japan |
| EWG | 德国ETF | Germany |
| EWU | 英国ETF | UK |
When updating templates, use these regex patterns to find and replace stale content:
# Week range (Chinese)
Find: \d+月\d+日-\d+月\d+日
Example: 1月12日-1月17日 → 1月19日-1月24日
# Report date (Chinese)
Find: 2026年\d+月\d+日
Example: 2026年1月17日 → 2026年1月24日
# ISO date
Find: 2026-\d{2}-\d{2}
Example: 2026-01-17 → 2026-01-24
# SPY price in text
Find: SPY \$\d+(\.\d+)?
Example: SPY $691.66 → SPY $698.50
# Price with comma (BTC)
Find: \$\d{2},\d{3}
Example: $95,535 → $96,800
# Weekly change
Find: [+-]\d+\.\d+%
Example: +0.14% → +0.99%
# In narrative
Find: 本周[+-]?\d+\.\d+%
Example: 本周+0.14% → 本周+0.99%
Find: 🔵 当前：2026年\d+月\d+日
Replace with current date
validate_data.py - Validates JSON against real-time sources (CoinGecko for crypto, Yahoo Finance for stocks/ETFs)validate_report.py - Validates report Python file against JSON (catches stale narrative content)--auto-fix flag to automatically update stale prices--section flag to validate specific sections