Iran Intelligence Radar
Overview
Iran Intelligence Radar is an OSINT-focused skill for detecting meaningful geopolitical signals from Persian-language discourse on X (Twitter). It scans configured keywords and accounts, filters and ranks high-engagement posts, translates content for multilingual analysis, computes escalation risk, and outputs a structured Markdown intelligence report.
This skill is designed for journalists, OSINT teams, geopolitical analysts, and monitoring operations that need a rapid understanding of Iranian online narratives.
Capabilities
- Monitor Persian-language tweets linked to Iran-related security, policy, and protest narratives.
- Detect high-signal content using keyword matching, engagement thresholds, and relevance ranking.
- Translate Persian posts into:
- English (
en) - Arabic (
ar) - Chinese (
zh)
- English (
- Classify tweet-level alert intensity (
LOW,MEDIUM,HIGH). - Detect trend spikes using keyword volume ratio (
current_count / historical_average). - Compute an Iran escalation score (
0-100) with severity levels:LOW(0-30)MEDIUM(31-60)HIGH(61-80)CRITICAL(81-100)
- Trigger automatic Telegram alerts when escalation conditions are met.
- Generate daily 24-hour intelligence briefings.
Default high-priority keywords include:
- حمله
- موشک
- تحریم
- غنی سازی
- اعتراض
- زن زندگی آزادی
- هسته ای
Invocation
Use any of the following command patterns:
run persian radarscan iran tweetsmonitor iran signals
Programmatic entrypoint:
from skills.persian_x_radar.agent import run_radar
result = run_radar(
user_id="demo_user",
query="run persian radar",
since_hours=6,
)
Typical execution flow:
- Billing and cooldown check
- X search and fallback retrieval
- Filtering and deduplication
- Translation and per-item alert classification
- Trending signal detection
- Escalation scoring
- Alert dispatch (Telegram/channel hooks)
- Markdown report generation
- Optional daily briefing assembly
Example Output
Intelligence Table (sample)
| # | Author | Time | Persian | English | Arabic | Chinese | Engagement | Link | Alert |
|---|---|---|---|---|---|---|---|---|---|
| 1 | @user123 | 2h ago | بحث درباره موشک... | Discussion about missiles... | نقاش حول الصواريخ... | 关于导弹的讨论... | 530 likes / 120 RT | https://x.com/... | HIGH |
| 2 | @iran_watch | 3h ago | گزارش هایی از اعتراض... | Reports of protests... | تقارير عن احتجاجات... | 有关抗议的报告... | 180 likes / 42 RT | https://x.com/... | MEDIUM |
Radar Summary (sample)
- Escalation score:
72 (HIGH) - Top signal:
missile discussion spike - Trending signals:
موشکspike detectedاعتراضvolume increase
Pricing
- Skill ID:
3092da48-a837-4288-94d6-458c6ef0b3e0 - Price per call:
$0.02 - Billing provider: SkillPay
Billing behavior:
- Each scan call is billable.
- Cooldown protection avoids duplicate charges within configured window.
- If balance is insufficient, the skill returns a payment link response:
{
"status": "payment_required",
"message": "Insufficient balance to run Persian X Radar.",
"price": 0.02,
"payment_link": "https://skillpay.me/pay/..."
}
Use Cases
- Real-time monitoring of missile, nuclear, sanctions, or protest narratives.
- Editorial intelligence support for breaking Iran-related developments.
- Geopolitical risk escalation tracking for operations/security teams.
- Multilingual situational awareness for non-Persian analysts.
- Daily strategic briefing generation from rolling social signal history.
Configuration
Primary configuration file:
skills/persian_x_radar/config.yaml
Key sections:
monitoringdefault_since_hoursheartbeat_minuteskeywordsaccounts
thresholdsmin_favesmin_retweets
translationlanguages(en,ar,zh)
trendingspike_thresholdmin_volumekeywords
alerts- channel and engagement thresholds
telegramenabledbot_tokenchat_id
billingskill_idprice_per_callcharge_cooldown_minutes
Common customization commands:
- Add keyword:
add keyword "سپاه" - Monitor account:
monitor account @BBCPersian - Change thresholds:
change alert threshold retweets > 200
This skill is suitable for deployment in AI skill marketplaces and agent orchestration platforms requiring deterministic billing, structured outputs, and operational alerting.