# Everest Supabase Operations

> Everest Supabase Operations

- Skill: `breverdbidder/everest-supabase-operations` (Agent Skill)
- Install (CLI): `npx skillmds@latest add breverdbidder/everest-supabase-operations`
- Raw SKILL.md: https://api.skillmd.com/api/skills/breverdbidder/everest-supabase-operations/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: breverdbidder (https://skillmd.com/u/breverdbidder)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/breverdbidder/everest-supabase-operations

---


# Everest Supabase Operations

## Connection

**Project**: mocerqjnksmhcjzxrewo.supabase.co
**Region**: us-east-1

```python
from supabase import create_client

SUPABASE_URL = "https://mocerqjnksmhcjzxrewo.supabase.co"
SUPABASE_KEY = os.environ["SUPABASE_KEY"]  # Service role key

supabase = create_client(SUPABASE_URL, SUPABASE_KEY)
```

## Key Tables

### BidDeed.AI Tables

| Table | Purpose | Rows |
|-------|---------|------|
| `historical_auctions` | Past auction data for ML | 1,393+ |
| `multi_county_auctions` | Current auction listings | Dynamic |
| `daily_metrics` | Pipeline performance | Daily |
| `insights` | System logs, decisions | Append-only |
| `activities` | User/system activities | 12+ |

### ZoneWise Tables

| Table | Purpose |
|-------|---------|
| `districts` | 273 zoning districts |
| `jurisdictions` | 17 Florida jurisdictions |
| `mcp_requests` | MCP server logs |

### Life OS Tables

| Table | Purpose |
|-------|---------|
| `tasks` | ADHD task tracking |
| `sprint_tasks` | Ralph Wiggum queue |
| `tax_records` | Tax optimization data |

### Shared Tables

| Table | Purpose |
|-------|---------|
| `claude_context_checkpoints` | Conversation state |
| `api_usage` | API cost tracking |

## Query Patterns

### Safe Query Building
```python
from scripts.query_builder import QueryBuilder

qb = QueryBuilder("historical_auctions")

# Select with filters
result = qb.select(
    columns=["case_number", "judgment_amount", "sale_price"],
    filters={"zip_code": "32937", "year": 2025},
    order_by="auction_date",
    limit=100
).execute()
```

### Insert with Validation
```python
from scripts.query_builder import safe_insert

# Validates against schema before insert
result = safe_insert(
    table="multi_county_auctions",
    data={
        "case_number": "05-2024-CA-012345",
        "parcel_id": "12345678",
        "judgment_amount": 150000,
        "auction_date": "2026-01-21"
    }
)
```

### Upsert Pattern
```python
result = supabase.table("multi_county_auctions").upsert(
    data,
    on_conflict="case_number"
).execute()
```

## Checkpoint Management

### Save Checkpoint
```python
from scripts.checkpoint_manager import save_checkpoint

save_checkpoint(
    conversation_id="conv_123",
    state={
        "current_task": "foreclosure_analysis",
        "properties_processed": 15,
        "pending_properties": ["12345678", "87654321"],
        "context_summary": "Analyzing Dec 3 auction..."
    },
    token_count=150000
)
```

### Load Checkpoint
```python
from scripts.checkpoint_manager import load_checkpoint

checkpoint = load_checkpoint(conversation_id="conv_123")
if checkpoint:
    state = checkpoint["state"]
    # Resume from saved state
```

### Auto-Checkpoint Trigger
```python
TOKEN_THRESHOLD = 150000  # 75% of 200K limit

def check_checkpoint_needed(current_tokens: int) -> bool:
    return current_tokens >= TOKEN_THRESHOLD
```

## Insights Logging

### Log Insight
```python
from scripts.insights_logger import log_insight

log_insight(
    category="ml_prediction",
    message="Third-party probability: 72%",
    data={
        "parcel_id": "12345678",
        "probability": 0.72,
        "confidence": "high"
    },
    level="info"
)
```

### Log Categories
- `pipeline`: Scraper/workflow events
- `ml_prediction`: Model predictions
- `decision`: BID/REVIEW/SKIP decisions
- `error`: Errors and failures
- `performance`: Timing and metrics
- `audit`: Security/compliance events

### Query Insights
```python
# Get recent errors
errors = supabase.table("insights")\
    .select("*")\
    .eq("level", "error")\
    .gte("created_at", "2026-01-20")\
    .execute()
```

## Table Schemas

### historical_auctions
```sql
CREATE TABLE historical_auctions (
    id SERIAL PRIMARY KEY,
    case_number TEXT UNIQUE NOT NULL,
    parcel_id TEXT,
    address TEXT,
    zip_code TEXT,
    judgment_amount NUMERIC,
    opening_bid NUMERIC,
    sale_price NUMERIC,
    sold_to_third_party BOOLEAN,
    plaintiff TEXT,
    plaintiff_category TEXT,
    auction_date DATE,
    property_type TEXT,
    assessed_value NUMERIC,
    bedrooms INT,
    bathrooms NUMERIC,
    building_sf INT,
    lot_sf INT,
    year_built INT,
    created_at TIMESTAMPTZ DEFAULT NOW()
);
```

### claude_context_checkpoints
```sql
CREATE TABLE claude_context_checkpoints (
    id SERIAL PRIMARY KEY,
    conversation_id TEXT NOT NULL,
    state JSONB NOT NULL,
    token_count INT,
    created_at TIMESTAMPTZ DEFAULT NOW(),
    expires_at TIMESTAMPTZ DEFAULT (NOW() + INTERVAL '7 days')
);

CREATE INDEX idx_checkpoints_conv ON claude_context_checkpoints(conversation_id);
```

### insights
```sql
CREATE TABLE insights (
    id SERIAL PRIMARY KEY,
    category TEXT NOT NULL,
    level TEXT DEFAULT 'info',
    message TEXT NOT NULL,
    data JSONB,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

CREATE INDEX idx_insights_category ON insights(category);
CREATE INDEX idx_insights_created ON insights(created_at DESC);
```

## RLS Policies

### Service Role (Full Access)
```sql
-- Used by backend/scripts
CREATE POLICY "Service role full access" ON historical_auctions
    FOR ALL USING (auth.role() = 'service_role');
```

### Anon Role (Read Only)
```sql
-- Used by public API
CREATE POLICY "Anon read access" ON districts
    FOR SELECT USING (true);
```

## Error Recovery

### Retry Pattern
```python
from scripts.query_builder import with_retry

@with_retry(max_attempts=3, backoff=2.0)
async def fetch_with_retry(table: str, filters: dict):
    return supabase.table(table).select("*").match(filters).execute()
```

### Connection Recovery
```python
from scripts.connection_manager import get_client

# Auto-reconnects on failure
client = get_client()  # Cached, reconnects if stale
```

## Migrations

### Run Migration
```bash
# Using Supabase CLI
supabase db push

# Or direct SQL
psql $DATABASE_URL -f migrations/001_add_column.sql
```

### Migration Naming
```
migrations/
├── 001_initial_schema.sql
├── 002_add_ml_features.sql
├── 003_add_checkpoints.sql
└── 004_add_indexes.sql
```

## Performance Tips

1. **Use indexes** for filtered columns
2. **Limit results** - never `SELECT *` without LIMIT
3. **Use RPC** for complex queries
4. **Batch inserts** - use `upsert` with arrays
5. **Cache lookups** - districts change rarely

## Integration

- **BidDeed.AI**: Historical data, predictions, reports
- **ZoneWise**: District data, MCP logs
- **Life OS**: Task tracking, tax records
- **Claude Sessions**: Context checkpoints