Portfolio Drift Monitor

Real-time monitoring of Kalshi portfolio positions with configurable alerts when positions move significantly. Ideal for active traders tracking exposure, P&L swings, and position concentration.

Overview

The Portfolio Drift Monitor tracks your Kalshi positions and alerts when any position moves beyond your configured threshold percentage since the last check. It:

• - Compares snapshots: Current positions vs. last recorded snapshot
• Detects drift: Flags positions that moved ≥ threshold (default 5%)
• Rate-limits checks: Prevents excessive API calls (configurable, default 60min interval)
• Formats alerts: Emoji indicators (📈/📉), directional arrows, price changes
• Persistent state: Stores snapshots locally at INLINECODE0

When to Use This Skill

• - You hold Kalshi positions overnight and want alerts if something moves sharply
• You want hourly drift checks between your morning and evening briefs
• You manage multiple positions and need to catch concentration risk early
• You want a lightweight risk monitoring layer that runs on a schedule without manual checking

Prerequisites

• - kalshi_python SDK: Install via INLINECODE1
• Kalshi API credentials: KALSHI_KEY_ID and KALSHI_KEY_PATH environment variables
• API key file: Located at path specified by KALSHI_KEY_PATH (typically ~/.kalshi/key.pem)

Configuration

Set these environment variables or edit defaults in your environment:

Variable	Default	Purpose
INLINECODE6	(required)	Your Kalshi API key ID from dev.kalshi.com
INLINECODE7

(required) | Path to your Kalshi private key file (ES256 PEM) |
| PORTFOLIO_DRIFT_THRESHOLD | 5.0 | Percentage change to trigger alert (e.g., 5 = 5%) |
| PORTFOLIO_DRIFT_INTERVAL | 60 | Minutes between checks (rate limiting, prevents API spam) |

How to Trigger

Use any of these phrases in conversation:

• - "check portfolio drift"
• "portfolio alert"
• "position monitor"
• "drift check"
• "kalshi positions"

How It Works

Step 1: Fetch Current Portfolio

The skill calls Kalshi's API to get your current open positions:

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This reads KALSHI_KEY_ID and KALSHI_KEY_PATH from environment, authenticates with Kalshi, and retrieves all open positions.

Step 2: Load Previous Snapshot

On first run, creates baseline snapshot. On subsequent runs, compares current positions with the last recorded snapshot stored at ~/.openclaw/state/portfolio_snapshot.json.

Step 3: Detect Drift

For each position, calculates percent change in:

• - Holdings (share count)
• Unrealized P&L (USD value)
• Price (avg entry price vs. current)

If any metric ≥ threshold, flags that position.

Step 4: Format and Output

Outputs drift alerts with:

• - Directional emoji: 📈 (up) or 📉 (down)
• Position symbol and side (YES/NO contract)
• Percentage change with sign (e.g., "+12.5%")
• Time since last check

Step 5: Update Snapshot

Saves current portfolio as new baseline for next check.

Output Format

Example output for a position that drifted:

CODEBLOCK1

Error Handling

• - First run: Creates baseline snapshot, no alerts
• API failure: Logs error, doesn't update snapshot
• Rate limit hit: Skips check if interval not elapsed
• No positions: Outputs "Portfolio is empty"

Command Examples

Check portfolio now (bypassing rate limit)

CODEBLOCK2

Check with custom threshold

CODEBLOCK3

Check and see full state file

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Threshold Tuning

Profile	Threshold	Interval	Use Case
Tight	3%	30 min	Active day trading, many positions
Standard

5% | 60 min | Default — balanced signal-to-noise | | Loose | 10% | 120 min | Long-term positions, fewer alerts | | News-reactive | 2% | 15 min | Event-driven trading (FOMC, elections) |

OpenClaw Ecosystem Integration

Risk management layer for the Prediction Market Trading Stack. Schedule hourly checks to catch position swings between Morning Briefs.

Scheduling:

skills:
  portfolio-drift-monitor:
    enabled: true
    schedule: "0 * * * *"  # Every hour
    timeout_seconds: 30

Connected Skill	How It Connects
Market Morning Brief	Morning/evening briefs bookend your day; drift alerts fill the gaps
Kalshi Command Center

Monitors positions opened through the command center |
| Kalshalyst | Tracks exposure on positions flagged by contrarian analysis |

Install the complete stack:
CODEBLOCK6

Performance & Cost

• - Runtime: <5 seconds per check
• API calls: 1 (Kalshi portfolio read)
• Cost: $0 (Kalshi free tier)
• State file: ~2KB (portfolio_snapshot.json)

Scaling

24 checks/day (hourly) = 24 Kalshi API calls. Well within free tier limits.

Debugging

Check logs and state:

CODEBLOCK7

Agent Bug-Fix Protocol

CRITICAL: When you (the agent) discover and fix a bug in any script during a conversation, you MUST write the fix to the source file on disk using file editing tools. Showing the fix in chat is NOT sufficient — the next scheduled run starts a fresh session and will not have your conversational fix.

Checklist after finding a bug:

1. 1. Edit the actual .py file on disk (e.g., ~/skills/portfolio-drift-monitor/scripts/portfolio_drift.py)
2. Also update the installed copy at INLINECODE18
3. Confirm both files are written before telling the user the fix is done
4. If the fix is significant, stage a git commit in INLINECODE19

Never say "fixed" if you only demonstrated the fix in conversation output.

Known Limitations

• - Kalshi-only: Currently monitors Kalshi positions only. Polymarket positions require separate tracking.
• Price-based drift: Drift is calculated on mid-market price changes, not on volume or open interest shifts.
• No alerting transport: Outputs to stdout. Your OpenClaw agent or a wrapper script handles delivery (iMessage, Slack, etc.).

Additional Resources

• - For complete configuration reference, see drift-config.md
• For API details, consult kalshi_python SDK docs

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Feedback & Issues

Found a bug? Have a feature request? Want to share results?

• - GitHub Issues: github.com/kingmadellc/openclaw-prediction-stack/issues
• X/Twitter: @KingMadeLLC

Part of the OpenClaw Prediction Stack — the first prediction market skill suite on ClawHub.