内容
# Simmer SDK
[](https://pypi.org/project/simmer-sdk/)
Simmer is the leading prediction market harness for AI agents. Autonomous agents place trades on venues like Polymarket, Kalshi and Hyperliquid through a unified API — with self-custody wallets, safety rails, and smart context.
- **AI-native trading platform** — designed for autonomous agents, with full support for manual trading too. Users install trading skills and let their agents trade autonomously.
- **$SIM simulated trading** — paper-trade with virtual currency before risking real funds.
- **Multi-venue** — trade Polymarket, Kalshi and Hyperliquid through one unified API.
## What's in this repo
| | |
|--|--|
| [`skills/`](skills/) | 28 skills an agent installs and runs. `skills/simmer/SKILL.md` is the canonical source for [simmer.markets/skill.md](https://simmer.markets/skill.md). |
| [`mcp/`](mcp/) | MCP server, published to npm as [`simmer-mcp`](https://www.npmjs.com/package/simmer-mcp). |
| [`simmer_sdk/`](simmer_sdk/) | Python SDK, published to PyPI as [`simmer-sdk`](https://pypi.org/project/simmer-sdk/). |
## Installation
```bash
pip install simmer-sdk
```
Get your API key from [simmer.markets/dashboard](https://simmer.markets/dashboard).
## Quick Start
### OpenClaw Skill Pattern (recommended)
Most Simmer users run trading skills inside [OpenClaw](https://openclaw.ai). The standard pattern uses a lazy singleton client and reads config from environment variables:
```python
import os
from simmer_sdk import SimmerClient
SKILL_SLUG = "my-skill-slug" # Must match your ClawHub slug
TRADE_SOURCE = f"sdk:{SKILL_SLUG}"
_client = None
def get_client(live: bool = False):
global _client
if _client is None:
venue = os.environ.get("TRADING_VENUE", "sim")
# `live` controls paper vs real execution and is a constructor arg, not a
# per-trade flag. live=False => paper preview (no real order placed).
_client = SimmerClient(api_key=os.environ["SIMMER_API_KEY"], venue=venue, live=live)
return _client
def run(live: bool = False):
client = get_client(live)
# Find markets. Unfiltered browse is windowed to the newest ~1,000 active
# markets — filter with sort="volume", q="...", or tags="..." to reach the rest.
markets = client.get_markets(status="active", sort="volume", limit=20)
# Get trading context (safeguards, slippage, conflict detection)
ctx = client.get_market_context(markets[0].id)
# Trade — always tag source and skill_slug
if not ctx.conflict and ctx.recommended_action != "hold":
result = client.trade(
market_id=markets[0].id,
side="yes",
amount=10.0,
source=TRADE_SOURCE,
skill_slug=SKILL_SLUG,
reasoning="Signal detected — buying YES"
)
print(f"{'PAPER: ' if not live else ''}Bought {result.shares_bought:.2f} shares")
if __name__ == "__main__":
import sys
run(live="--live" in sys.argv)
```
Set environment variables:
```bash
export SIMMER_API_KEY=sk_live_...
export TRADING_VENUE=sim # sim | polymarket | kalshi
export WALLET_PRIVATE_KEY=0x... # Required for Polymarket self-custody
```
> **Default to dry-run.** Skills should require `--live` to execute real trades. Paper-trade with `$SIM` until your edge is consistent, then graduate to real money.
### Raw SDK
For developers building custom integrations:
```python
from simmer_sdk import SimmerClient
client = SimmerClient(api_key="sk_live_...")
# Browse markets (unfiltered browse is windowed to the newest ~1,000 active
# markets — use sort="volume", q="...", or tags="..." for discovery)
markets = client.get_markets(sort="volume", limit=10)
for m in markets:
print(f"{m.question}: {m.current_probability:.1%}")
# Trade with $SIM (virtual currency)
result = client.trade(market_id=markets[0].id, side="yes", amount=10.0)
print(f"Bought {result.shares_bought:.2f} shares for ${result.cost:.2f}")
# Check P&L
for p in client.get_positions():
print(f"{p.question[:50]}: P&L ${p.pnl:.2f}")
```
## Trading Venues
| Venue | Currency | Description |
|-------|----------|-------------|
| `sim` | $SIM (virtual) | Default. Paper trading on Simmer's LMSR markets. |
| `polymarket` | USDC.e (real) | Real trades on Polymarket (Polygon). Requires `WALLET_PRIVATE_KEY`. |
| `kalshi` | USDC (real) | Real trades on Kalshi. Requires Pro plan. |
```python
# Paper trading (default)
client = SimmerClient(api_key="sk_live_...", venue="sim")
# Real trading on Polymarket
client = SimmerClient(api_key="sk_live_...", venue="polymarket")
# Read-only validation/status client. Does not process constructor-time risk exits.
client = SimmerClient.readonly(api_key="sk_live_...", venue="polymarket")
# Override venue for a single trade
client.trade(market_id, side="yes", amount=10.0, venue="polymarket")
```
`TRADING_VENUE` environment variable is read at client init — OpenClaw skills use this to select venue at startup without code changes.
> **Constructor side effect:** for live Polymarket clients with `WALLET_PRIVATE_KEY` or `OWS_WALLET`, regular `SimmerClient(...)` construction checks pending risk alerts and may submit stop-loss/take-profit exit orders. This is intentional for self-custody safety: Simmer's server cannot sign those exits. Use `SimmerClient.readonly(...)` for API-key validation, preflight/status checks, and other non-trading paths.
> **Spread caveat:** $SIM fills instantly (AMM, no spread). Real venues have orderbook spreads of 2–5%. Target edges >5% in $SIM before graduating to real money.
> **Polymarket order types:** omit `order_type` for the SDK/server smart default: buys use `FAK` (fill what is available immediately), sells use `GTC` (rest on the book to improve fill rate on thin books). For structurally thin markets or maker-style limit entries, pass `order_type="GTC"` and an explicit `price`.
### Paper trading on real venues
Pass `live=False` to simulate trades with real market prices — no wallet or USDC required. For Polymarket, fills model the CLOB bid-ask spread for realistic P&L. Resolved markets auto-settle (winning shares pay $1, losers $0).
```python
client = SimmerClient(
api_key="sk_live_...",
venue="polymarket",
live=False, # Simulate fills, no real money
starting_balance=10_000.0 # Virtual capital (default: 10,000)
)
result = client.trade(market_id=markets[0].id, side="yes", amount=50.0,
reasoning="Testing strategy")
print(f"Filled {result.shares_bought:.2f} shares (simulated)")
# Portfolio summary
summary = client.get_paper_summary()
print(f"Balance: ${summary['balance']:.2f}, P&L: ${summary['total_pnl']:.2f}")
```
**Graduation path:** `sim` (instant fills, no spread) → `polymarket` + `live=False` (real prices, spread modeled) → `polymarket` live (real USDC).
## Backtesting
The three modes above are all *live-forward*. To test a strategy on **historical** data before risking capital, backtest the skill bundle:
```bash
pip install 'simmer-sdk[backtest]'
# Try it offline — bundled 10-market demo slice, no data download:
simmer backtest --demo
# Backtest your own skill over a window — the tape is fetched + cached for you:
simmer backtest ./my-skill --entrypoint run.py \
--t0 2026-03-01 --t1 2026-03-08 --cadence 12h --out report.json
# ...or by duration, and with your own local slice (BYO):
simmer backtest ./my-skill --entrypoint run.py --window 30d
simmer backtest ./my-skill --entrypoint run.py --tape ./slice --t0 2026-03-01 --t1 2026-03-08
# Narrow the fetched slice to a topic — matches question OR slug, applied
# before the volume cap, so a niche topic isn't crowded out by high-volume noise:
simmer backtest ./weather-skill --entrypoint run.py \
--t0 2026-03-01 --t1 2026-03-08 --q temperature
```
The engine replays your **unmodified** skill against a frozen, look-ahead-safe
replay server (one subprocess per tick) and reports pnl, hit rate, max drawdown,
trades, baselines (buy-and-hold-YES / random), realism gaps, and a reproducible
`config_hash`. Programmatic equivalent:
```python
from simmer_sdk.backtest import run_backtest
# tape omitted => the window slice is fetched from the tape service and cached.
report = run_backtest("./my-skill", entrypoint="run.py",
t0="2026-03-01", t1="2026-03-08", cadence="12h")
print(report["summary"]["pnl"], report["summary"]["hit_rate"])
```
> Backtests use trade-tape prices (no orderbook), so they model decision quality,
> not execution realism — every report lists its `realism_gaps`. The window slice
> is fetched from Simmer's tape service and cached under `~/.simmer/tapes/`; pass
> `--tape <dir>` to use your own. Data coverage currently ends ~2026-05-05.
## Key Methods
| Method | Description |
|--------|-------------|
| `get_markets()` | List markets (filter by status, source, venue, tags, keyword) |
| `trade()` | Buy or sell shares |
| `get_positions()` | All positions with P&L |
| `get_held_markets()` | Map of market_id → source tags for held positions |
| `check_conflict()` | Check if another skill holds a position on a market |
| `get_open_orders()` | Open GTC/GTD orders on the CLOB |
| `maker_rewards_status(market_id)` | Polymarket liquidity-rewards config: max spread, daily pool, eligibility |
| `get_portfolio(venue="all")` | Portfolio summary with per-venue buckets (sim/polymarket/kalshi/total) |
| `get_market_context(market_id, venue="all")` | Per-venue positions + trading safeguards |
| `get_trades(venue="all")` | Trade history merged across venues, each row tagged with venue |
| `get_price_history()` | Price history for trend detection |
| `import_market()` | Import a Polymarket market by URL |
| `import_kalshi_market()` | Import a Kalshi market by URL |
| `list_importable_markets()` | Discover markets available to import |
| `check_market_exists()` | Check if a market is already on Simmer (no quota cost) |
| `set_monitor()` | Set stop-loss / take-profit on a position |
| `cancel_order()` | Cancel a single open order by ID |
| `cancel_market_orders()` | Cancel all open orders on a market (optional side filter) |
| `cancel_all_orders()` | Cancel all open orders across all markets |
| `create_alert()` | Price alerts with optional webhook |
| `register_webhook()` | Push notifications for trades, resolutions, price moves |
| `redeem()` | Redeem a specific winning Polymarket position |
| `auto_redeem()` | Scan all positions and redeem any winning ones automatically |
| `get_paper_summary()` | Paper mode portfolio summary (balance, P&L, positions) |
| `get_settings()` / `update_settings()` | Configure trade limits and notifications |
| `link_wallet()` | Link external EVM wallet for Polymarket |
| `set_approvals()` | Set Polymarket token approvals |
| `activate_polymarket_dw(agent_id=None)` | Set Polymarket Deposit Wallet on-chain CLOB approvals — user-primary (no arg) or per-agent (`agent_id=...`). See note. |
| `readonly()` | Constructor for validation/status clients that must not process constructor-time risk exits or submit orders |
| `troubleshoot()` | Look up any error and get a fix (no auth required) |
> **Per-agent wallets (Elite tier):** activating a per-agent (Elite dedicated) wallet takes **two** calls, approvals first: `activate_polymarket_dw(agent_id=...)` sets the deposit wallet's on-chain CLOB approvals, then `update_agent_wallet_creds(...)` caches the CLOB creds. OWS callers use `update_agent_wallet_creds(ows_wallet_name="...")`; raw-key callers with `WALLET_PRIVATE_KEY` use `update_agent_wallet_creds(agent_id="...")`. **Both approvals and cached creds are required before trading** — caching creds alone does not set on-chain allowances, so trades fail at the relayer with "insufficient allowance". See the `simmer-wallet-setup` skill for the full flow. (`set_approvals()` is the user-primary EOA path and is a no-op for per-agent deposit wallets.)
**Tip — don't pre-round prices.** simmer-sdk ≥ 0.17.1 automatically rounds the price to each Polymarket market's tick grid. Pass your raw computed price to `client.trade(..., price=p)` and the SDK handles the rest. Pre-rounding with a hardcoded tick (e.g. `round(price, 3)`) will silently produce wrong values for markets at different tick sizes.
**Error handling:** All SDK 4xx responses include a `fix` field with actionable instructions when the error matches a known pattern. You can also call `POST /api/sdk/troubleshoot` with `{"error_text": "..."}` to look up any error.
Full API reference with parameters, examples, and error codes: **[simmer.markets/docs.md](https://simmer.markets/docs.md)**
## Skill Builder Utilities
The SDK ships two helper modules for skill authors. Prefer these over rolling your own — they encode patterns from top traders and external research.
### Position sizing — `simmer_sdk.sizing`
Kelly Criterion + Expected Value sizing for binary prediction markets. Default is fractional Kelly (0.25x) with an EV gate, so trades below your edge threshold return `0.0` and the skill can simply skip them.
```python
from simmer_sdk import SimmerClient
from simmer_sdk.sizing import size_position
client = SimmerClient()
bankroll = client.get_portfolio()["available_balance"]
amount = size_position(
p_win=0.70, # your model's probability
market_price=0.55, # current YES price
bankroll=bankroll,
min_ev=0.03, # skip trades with edge < 3%
)
if amount > 0:
client.trade(market_id=..., side="yes",
amount=amount, reasoning="Kelly: 70% vs 55%, +15% edge")
```
| Function | Purpose |
|----------|---------|
| `size_position(p_win, market_price, bankroll, method=, kelly_multiplier=, min_ev=, max_fraction=)` | Returns dollar amount to trade. `0.0` when edge ≤ `min_ev`, Kelly is negative, or inputs are invalid. |
| `kelly_fraction(p_win, market_price)` | Raw Kelly fraction `(p - c) / (1 - c)`. |
| `expected_value(p_win, market_price)` | Edge per share (`p_win - market_price`). |
| `SIZING_CONFIG_SCHEMA` | Drop-in `CONFIG_SCHEMA` fragment exposing `SIMMER_POSITION_SIZING`, `SIMMER_KELLY_MULTIPLIER`, `SIMMER_MIN_EV` env vars. |
Methods: `"fractional_kelly"` (default, multiplier 0.25), `"kelly"` (full, aggressive), `"fixed"` (uses `kelly_multiplier` as a flat fraction). For NO bets pass `p_win=1-p_yes` and `market_price=1-yes_price`.
## Auto-Redeem
When a Polymarket market resolves and your side wins, the CTF tokens in your wallet must be redeemed to claim the USDC.e payout. Auto-redeem handles this automatically each cycle.
```python
# Call at the start of each cycle to claim any pending winnings
results = client.auto_redeem()
for r in results:
if r["success"]:
print(f"Redeemed {r['market_id']} ({r['side']}): {r['tx_hash']}")
```
- Fetches positions where `redeemable: true` and `redeemable_side` is set (Polymarket only)
- For self-custody wallets (`WALLET_PRIVATE_KEY`): signs and broadcasts on-chain
- For managed wallets: server handles signing, no local key needed
- Never raises — safe to call every cycle
Auto-redeem can be toggled per-agent from the Simmer dashboard.
## Skills
Pre-built trading strategies are published on [ClawHub](https://clawhub.ai) and listed in the Simmer registry. Browse and install at **[simmer.markets/skills](https://simmer.markets/skills)**.
```bash
# Install a skill via ClawHub CLI
clawhub install polymarket-weather-trader
```
Skills in this repo (`skills/`) are the official Simmer-maintained strategies. See [docs.simmer.markets/skills/building](https://docs.simmer.markets/skills/building) for the full guide to building, remixing, and publishing your own.
## Resources
| | |
|--|--|
| **Platform** | [simmer.markets](https://simmer.markets) |
| **API Reference** | [docs.simmer.markets](https://docs.simmer.markets) |
| **Onboarding Guide** | [simmer.markets/skill.md](https://simmer.markets/skill.md) |
| **Skills Registry** | [docs.simmer.markets/skills](https://docs.simmer.markets/skills/overview) |
| **ClawHub** | [clawhub.ai](https://clawhub.ai) |
| **MCP Server** | `npm install -g simmer-mcp` — docs + error troubleshooting as MCP resources ([npm](https://www.npmjs.com/package/simmer-mcp)) |
| **Telegram** | [t.me/+m7sN0OLM_780M2Fl](https://t.me/+m7sN0OLM_780M2Fl) |
## Contributing
SDK improvements and bug fixes are welcome. If you've hit an edge case with `SimmerClient` or have a useful addition, open a PR.
- **Skills** belong on [ClawHub](https://clawhub.ai), not this repo — see [docs.simmer.markets/skills/building](https://docs.simmer.markets/skills/building)
- **API bugs or feature requests** → open an issue first
- **AI-assisted PRs welcome** — just note it in the PR description
- Keep PRs focused on one thing
See [CONTRIBUTING.md](./CONTRIBUTING.md) for the full guide.
## License
MIT
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