---
name: warsat
description: "On-demand OSINT military/intelligence scanner with orbital awareness platform. Monitors air, sea, land, cyber, proxy, and infrastructure domains for geopolitical developments, force movements, and conflict indicators. Chains through delta comparison and prediction engine for intelligence-grade analysis. Use when the user says 'warsat scan', 'warsat status', 'warsat on', 'warsat off', or 'warsat predict'. Supports category-specific scans: 'warsat scan air', 'warsat scan sea', 'warsat scan land', 'warsat scan cyber', 'warsat scan proxy', 'warsat scan infra'."
---

# Warsat -- Orbital Awareness Platform

Warsat is a chained intelligence system: scan → delta comparison → orbital platform → prediction output. Every scan flows through the full pipeline automatically.

## Quick Reference

| Command | Action |
|---------|--------|
| `warsat on` | Enable master switch |
| `warsat off` | Killswitch -- all scans stop |
| `warsat status` | Show switch state + last scan summary |
| `warsat scan` | Run FULL PIPELINE: scan → delta → orbital → predict |
| `warsat scan air` | Air assets only (pipeline still runs) |
| `warsat scan sea` | Naval assets only (pipeline still runs) |
| `warsat scan land` | Ground/defense/nuclear only |
| `warsat scan cyber` | Cyber/info/economic only |
| `warsat scan proxy` | Proxy forces only |
| `warsat scan infra` | Infrastructure/diplomatic only |
| `warsat predict` | Skip scan, run orbital platform on existing data |
| `warsat baseline` | Show current baseline summary |

## CHAINED PIPELINE (Auto-Executed on Every Scan)

```
┌─────────────────────────────────────────────────────────────────┐
│  STEP 1: SCAN                                                   │
│  • Load monitors.json (45 monitors across 6 domains)           │
│  • Run web_search queries for each domain                       │
│  • Parse results, assign alert levels                           │
│  • Save to memory/warsat/scan-log.json                          │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────────┐
│  STEP 2: DELTA COMPARISON                                       │
│  • Run: python3 scripts/warsat-delta.py                         │
│  • Load baseline.md (known events, cumulative figures)          │
│  • Compare scan findings vs baseline                             │
│  • Filter out known events (fuzzy match, figure comparison)     │
│  • Output: Only NEW findings (deltas)                           │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────────┐
│  STEP 3: ORBITAL PLATFORM                                       │
│  • Run: python3 scripts/warsat-orbital.py --mode analyze        │
│                                                                 │
│  PLANETARY CORE:                                                 │
│  ┌─────────────────────┐  ┌─────────────────────┐               │
│  │ LEADING INDICATOR   │  │ CONTRADICTION        │               │
│  │ TRACKER             │  │ DETECTOR             │               │
│  │ • 19 indicators     │  │ • Status reversals   │               │
│  │ • Confidence weight │  │ • Figure mismatches  │               │
│  │ • Lead times        │  │ • Resolution prompts│               │
│  └─────────────────────┘  └─────────────────────┘               │
│                                                                 │
│  SATELLITE FUNCTIONS:                                           │
│  • Impact Scorer (1-10 significance rating)                      │
│  • Event Classifier (MILITARY/DIPLOMATIC/ECONOMIC/etc.)          │
│  • Trend Detector (frequency, direction, acceleration)          │
│                                                                 │
│  PREDICTION ENGINE:                                             │
│  • Synthesizes all inputs into forward-looking predictions      │
│  • Confidence-weighted output                                   │
│  • Grand pontification narrative                                 │
└───────────────────────────┬─────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────────┐
│  STEP 4: OUTPUT REPORT                                          │
│                                                                 │
│  Present to user:                                                │
│  1. DELTA FINDINGS (new events only)                            │
│  2. PREDICTIONS (confidence bars, indicators)                   │
│  3. GRAND PONTIFICATION (narrative assessment)                  │
│  4. THREAT LEVEL (LOW → CRITICAL)                                │
│                                                                 │
│  Ask: "Update baseline with new confirmed findings?"            │
└─────────────────────────────────────────────────────────────────┘
```

## Execution Flow (Detailed)

### Phase 1: Scan
1. Read switch file. If OFF, respond "Warsat is OFF" and stop.
2. Load monitor definitions from `references/monitors.json`.
3. For each monitor in requested category:
   - Run web_search queries from monitor's `sources` list.
   - Assign alert level based on findings vs `alertLevels` thresholds.
   - Capture key finding, source, and significance.
4. Save raw scan results to `memory/warsat/scan-log.json`.

### Phase 2: Delta Comparison
1. Run `python3 scripts/warsat-delta.py` with scan results as input.
2. Load baseline from `memory/warsat/baseline.md`.
3. Compare findings:
   - Fuzzy match (0.75 threshold) for event similarity.
   - Figure comparison (10% change threshold).
   - Timestamp comparison for event dating.
4. Output only findings NOT in baseline (NEW information).

### Phase 3: Orbital Platform
1. Run `python3 scripts/warsat-orbital.py --mode analyze`.
2. Leading Indicator Tracker:
   - Load `memory/warsat/indicators.json`.
   - Check which indicators are at HIGH/CRITICAL.
   - Match active indicators to prediction templates.
3. Contradiction Detector:
   - Compare delta findings vs baseline.
   - Flag status reversals, figure mismatches.
   - Generate resolution prompts for contradictions.
4. Satellite Functions:
   - Impact Scorer: Rate significance (1-10).
   - Event Classifier: Categorize into awareness buckets.
   - Trend Detector: Identify patterns over time.
5. Prediction Engine:
   - Synthesize all inputs.
   - Generate confidence-weighted predictions.
   - Produce grand pontification narrative.

### Phase 4: Output
1. Present combined report to user.
2. Show: deltas, predictions, threat level, narrative.
3. Ask user to confirm baseline update for new findings.

## Output Format

```
🛰️ WARSAT2 — ORBITAL AWARENESS REPORT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

THREAT LEVEL: [CRITICAL|HIGH|ELEVATED|MODERATE|LOW]
Active Indicators: [X] ([Y] CRITICAL)
Contradictions Detected: [Z]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DELTA FINDINGS (NEW ONLY)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[Level emoji] [IMPACT SCORE]/10 — [Category]
- Finding: [new event description]
- Source: [where found]
- Indicator Match: [which leading indicator triggered]
- Contradiction: [if applicable, what baseline entry conflicts]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
PREDICTIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[Confidence bar] [XX%] — [Prediction text]
Supported by: [indicator names]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GRAND PONTIFICATION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[Narrative paragraph synthesizing threat level, active
indicators, high-confidence predictions, and trajectory
assessment. Grand but grounded.]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
BASELINE UPDATE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[X] new findings pending baseline confirmation.
Ask user: "Update baseline with confirmed findings?"
```

## Alert Levels

| Level | Emoji | Meaning |
|-------|-------|---------|
| CRITICAL | 🔴 | Imminent or active -- requires immediate attention |
| HIGH | 🟠 | Significant -- likely precursor to action |
| MEDIUM | 🟡 | Notable -- worth monitoring |
| LOW | 🟢 | Baseline -- no action needed |

## Threat Levels (Orbital Output)

| Level | Meaning |
|-------|---------|
| CRITICAL | Multiple critical indicators active, high-confidence predictions of escalation |
| HIGH | Significant indicator activity, predictions indicate near-term developments |
| ELEVATED | Above-baseline activity, partial prediction matches |
| MODERATE | Stable situation, some indicators active |
| LOW | Baseline conditions, no significant indicators |

## Leading Indicators (Orbital Core)

The orbital platform tracks 19 leading indicators across domains:

| Domain | Indicators |
|--------|------------|
| **AIR** | B-2 deployment, B-52 overflight, Tanker surge, ISR orbit |
| **SEA** | Carrier position, Amphibious deployment, Destroyer density |
| **DIPLOMATIC** | Shuttle intensity, Coalition formation |
| **ECONOMIC** | Oil price, Supply chain disruption |
| **PROXY** | Proxy activation, Ceasefire adherence |
| **HUMANITARIAN** | Civilian casualties, Humanitarian access |

Each indicator has:
- Historical correlation with specific outcomes
- Confidence weight (0.0-1.0)
- Lead time (hours to weeks)
- Current status (LOW/MEDIUM/HIGH/CRITICAL)

## File Layout

```
skills/warsat/
├── SKILL.md                     (this file)
└── references/
    └── monitors.json             (45 monitor definitions)

scripts/
├── warsat-delta.py               (baseline comparison)
└── warsat-orbital.py             (LI tracker, CD, satellites, predictions)

memory/warsat/
├── baseline.md                   (ground truth — known events, figures)
├── indicators.json               (leading indicator library)
├── contradictions.json            (detected contradictions)
├── trends.json                   (trend history)
├── scan-log.json                 (scan history)
└── history/                      (change detection history)
```

## Notes

- Warsat is designed for on-demand use. Run scans when needed.
- Every scan automatically flows through the full pipeline — no manual chaining required.
- The orbital platform enriches raw scan data with prediction-grade intelligence.
- Contradictions flag when new findings conflict with baseline — ask user to resolve.
- Leading indicators provide early warning based on historical patterns.
- Grand pontification synthesizes everything into a forward-looking narrative.