Provides a Telegram bot interface for monitoring prediction market theses and executing trades directly through the messaging platform.
SimpleFunctions CLI (sf)
Prediction market intelligence CLI. Build causal thesis models, scan Kalshi/Polymarket for mispricings, detect edges, and trade — all from the terminal.
Quick Start
npm install -g @spfunctions/cli
sf setup # interactive config wizard
sf list # see your theses
sf context <id> --json # get thesis state as JSONSetup
Interactive (recommended)
sf setupThis walks you through:
SF API key (required) — get one at simplefunctions.dev
Kalshi credentials (optional) — for positions, trading, and orderbook data
Trading mode (optional) — enable
sf buy/sf sellcommands
Config is saved to ~/.sf/config.json. Environment variables override config values.
Manual
export SF_API_KEY=sf_live_xxx # required
export KALSHI_API_KEY_ID=xxx # optional, for positions/trading
export KALSHI_PRIVATE_KEY_PATH=~/.ssh/kalshi.pem # optional, for positions/tradingVerify
sf setup --check # show current config status
sf list # should show your thesesCommands
Thesis Management
Command | Description |
| List all theses with status, confidence, and update time |
| Full thesis details: causal tree, edges, positions, last evaluation |
| Compact context snapshot (primary command for agents) |
| Create a new thesis (waits for formation by default) |
| Inject a signal (news, observation) for next evaluation |
| Trigger deep evaluation with heavy model |
| Make thesis publicly viewable |
| Remove from public view |
Market Exploration (no auth required)
Command | Description |
| Search Kalshi markets by keyword |
| List all markets in a series |
| Get single market detail |
| Browse public theses |
Portfolio & Trading (requires Kalshi credentials)
Command | Description |
| Top edges across all theses — what to trade now |
| Current positions with P&L and edge overlay |
| Account balance |
| Resting (open) orders |
| Recent trade fills |
| P&L over time with thesis event annotations |
| Settled contracts with final P&L |
| Market liquidity scanner by topic |
Trading (requires sf setup --enable-trading)
Command | Description |
| Buy contracts |
| Sell contracts |
| Cancel order(s) |
| Request for quote on large orders |
Analysis
Command | Description |
| What-if scenario: "if node X drops to 10%..." |
| Evaluation history stream |
| Market distribution forecast (P50/P75/P90) |
| Interactive TUI portfolio overview |
Interactive Modes
Command | Description |
| Interactive agent with natural language + tool calling |
| Telegram bot for monitoring and trading |
JSON Output
Most commands support --json for machine-readable output:
sf list --json
sf context f582bf76 --json
sf edges --json
sf scan "oil" --json
sf get f582bf76 --jsonFor AI Agents
If you are an AI coding agent (Claude, GPT, OpenClaw, Cursor, etc.), follow these steps:
Step 1: Install and configure
npm install -g @spfunctions/cli
sf setup --key sf_live_YOUR_KEY_HEREIf sf setup is not available or you cannot run interactive commands:
export SF_API_KEY=sf_live_YOUR_KEY_HEREStep 2: Verify it works
sf listExpected output (table format):
ID Status Conf Updated Title
f582bf76 active 82% Mar 12 11:13 Oil prices will exceed $100...
a1b2c3d4 active 65% Mar 11 09:30 Fed will cut rates by June...If you see theses, the CLI is working. If you see an error, check that SF_API_KEY is set correctly.
Step 3: Get thesis context (most important command)
sf context <thesisId> --jsonThis returns a JSON object with the complete thesis state:
{
"thesisId": "f582bf76-3113-4208-b0c1-...",
"thesis": "Oil prices will exceed $100 by end of 2026",
"title": "Oil Bull Thesis",
"status": "active",
"confidence": 0.82,
"causalTree": {
"rootClaim": "Oil prices will exceed $100",
"nodes": [
{
"id": "n1",
"label": "Supply disruption",
"probability": 0.75,
"importance": 0.6,
"depth": 0
}
]
},
"edges": [
{
"marketId": "KXWTIMAX-26DEC31-T100",
"market": "Will oil exceed $100 by Dec 2026?",
"venue": "kalshi",
"direction": "yes",
"marketPrice": 35,
"thesisPrice": 55,
"edge": 20,
"confidence": 0.8
}
],
"lastEvaluation": {
"summary": "Supply concerns rising due to...",
"newConfidence": 0.82,
"confidenceDelta": 0.03
}
}Key fields:
confidence— overall thesis probability (0 to 1)edges[].edge— mispricing size in cents (positive = market underpriced vs thesis)edges[].marketPrice— current market price in cents (0-100)edges[].thesisPrice— what the thesis model thinks the price should belastEvaluation.summary— human-readable summary of latest analysis
Step 4: Other useful commands
# Inject a signal for the thesis to consider in its next evaluation
sf signal <thesisId> "Breaking: OPEC announces production cut" --type news
# View top edges (mispricings) across all theses
sf edges --json
# Search Kalshi markets by keyword
sf scan "recession" --json
# Trigger a deep re-evaluation
sf evaluate <thesisId>
# What-if analysis: what happens if a node probability changes?
sf whatif <thesisId>Common patterns for agents
Monitor a thesis:
sf context <id> --json # poll periodically, check confidence changesReact to news:
sf signal <id> "Reuters: Iran nuclear deal collapses" --type news
sf evaluate <id> # trigger re-evaluation after injecting signal
sf context <id> --json # read updated stateFind trading opportunities:
sf edges --json # get top mispricings sorted by edge sizeError handling
"API key required" — set
SF_API_KEYenv var or runsf setup --key <key>"Thesis not found" — use
sf listto get valid thesis IDs. IDs can be short prefixes (first 8 chars)"Kalshi not configured" — positions/trading commands need Kalshi credentials via
sf setupExit code 0 — success. Exit code 1 — error (message printed to stderr)
Local Development
cd cli
npm install
npm run dev -- list # run without building
npm run build # compile to dist/
npm run test # run unit tests
npm link # install as global 'sf' command
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