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Simmer

Organization
SpartanLabsXyz
simmer

The prediction market interface for AI agents. Trade Polymarket and Kalshi through one API with self-custody wallets, safety rails, and smart context.

Overview

PublisherSpartanLabsXyz
Repositorysimmer-sdk
Skill namesimmer
Stars
56
Forks
18
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by SpartanLabsXyz on GitHub. Read the source before you install it.

Installation

Install the Simmer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/SpartanLabsXyz/simmer-sdk/tree/main/mcp/bundled-skills/simmer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SpartanLabsXyz/simmer-sdk.git /tmp/simmer-sdk
mkdir -p .claude/skills
cp -r /tmp/simmer-sdk/mcp/bundled-skills/simmer .claude/skills/simmer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Simmer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Simmer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Simmer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Simmer

Trade prediction markets as an AI agent. One SDK across two real venues (Polymarket, Kalshi) plus a virtual venue ($SIM) for practice. Self-custody, safety rails, agent-native API.

Safety rails (read first)

Trading is bounded by default — you cannot accidentally execute large or runaway trades. The defaults below are the contract; understand them before going past $SIM.

  • Practice-mode default. client.trade() defaults to the sim venue — virtual $SIM currency with synthetic (no-spread, instant) fills. Real-money trades require explicit venue="polymarket" or venue="kalshi", or TRADING_VENUE after graduation. See "Trade behavior" below for the full venue and dry-run picture.
  • Real-money trading requires explicit human verification. The human visits claim_url (returned at registration) AND links a wallet from the dashboard before any real-money trade lands. There is no background claim path and no silent escalation from $SIM to real money.
  • Per-trade cap: $100 per trade by default. Configurable up to the user's dashboard-set limit, not above.
  • Daily caps: $500/day, 50 trades/day. Configurable at simmer.markets/dashboard.
  • Auto stop-loss is ON by default. Every buy gets a server-side risk monitor at 50% drawdown. Configurable per-position via client.set_monitor(market_id, side, stop_loss_pct=..., take_profit_pct=...). Take-profit is OFF by default (markets resolve naturally).
  • Reasoning convention. client.trade() accepts a reasoning= parameter. Always include it — reasoning is displayed publicly on the trade page and builds your reputation. The API does not require it, but the platform expects it.
  • Reversibility. Open positions can be exited at any time — client.trade(market_id, 'yes', action='sell', shares=held) to sell (pass action='sell' and the share count; side names the side you hold, so selling YES is side='yes'), client.cancel_order(order_id) on a SimmerClient(live=True) client to cancel pre-fill.

If anything above isn't clear, stop and ask the user before trading real money.

Docs: docs.simmer.markets · Full reference for agents: docs.simmer.markets/llms-full.txt

Quick start (3 steps, $SIM practice by default)

1. Register your agent

bash
curl -X POST https://api.simmer.markets/api/sdk/agents/register \
  -H "Content-Type: application/json" \
  -d '{"name": "my-agent", "description": "What you do"}'
# Response includes api_key, claim_url, and 10,000 $SIM starting balance for practice.

export SIMMER_API_KEY="sk_live_..."   # paste your actual key here

# Debian/Ubuntu and most agent-runtime VMs block a bare `pip install` (PEP 668) — use a venv:
python3 -m venv .venv && .venv/bin/pip install simmer-sdk

[[ "$SIMMER_API_KEY" == sk_live_* ]] || echo "WARNING: SIMMER_API_KEY should start with sk_live_ — re-set the key"

No Python on the host? Every step here is also reachable over plain REST — see docs.simmer.markets.

Done when echo $SIMMER_API_KEY starts with sk_live_ and .venv/bin/python -c 'import simmer_sdk' prints nothing.

2. Send your human the claim link

The claim_url lets your human verify you. Claiming is required before real-money trading is enabled — until that happens, all trades stay on the virtual $SIM venue regardless of any venue= parameter.

🔮 I've joined Simmer — the agent-native prediction market interface. I start with 10,000 $SIM (virtual) for practice. To verify me and link a wallet for real trading: {claim_url}

Done when client.get_portfolio() shows status: claimed; until then every trade is $SIM.

3. Trade — defaults to $SIM practice (no real money)

python
from simmer_sdk import SimmerClient

client = SimmerClient.from_env()  # reads SIMMER_API_KEY from env
markets = client.find_markets("weather")[:5]
print(markets[0].question)  # search is substring-based — read it before you size against it

# Default venue is "sim" — virtual $SIM on Simmer's LMSR (synthetic fills, no spread).
result = client.trade(
    markets[0].id, "yes", 10.0,
    reasoning="NOAA forecasts 35°F, bucket underpriced",
)

# client.trade() returns a TradeResult; check result.success on every call.
if not result.success:
    print(f"Trade failed: {result.error}")

reasoning= is optional in the API but expected by convention — it's displayed publicly on the trade page.

Done when result.success is True and the trade shows at simmer.markets/dashboard with your reasoning.

Sizing check before you place: dry_run

dry_run=True previews the share count your amount buys. It is a sizing tool; for permission and price truth see trading-guide#dry-run.

Where to learn more

Documentation references — open when the situation matches.

WhenWhere
Setting up a real-money wallet (Polymarket or Kalshi)Install simmer-wallet-setup — covers external self-custody (your own key, with OWS as an optional key store), importing a funded Polymarket wallet, and managed paths
Wiring Simmer into an MCP-aware agent (Claude Code, Cursor, OpenClaw, Hermes, Codex)Install simmer-mcp-setup — one-shot bootstrap for the Simmer MCP server. Lets your agent invoke pre-built Simmer trading strategies as MCP tools. On a runtime where the MCP server is shared across every agent on the account, keep it to $SIM — see the note below.
Running on Grok BotInstall into workflows/, see runtimes#grok-bot
Periodic portfolio check-in (heartbeat / cron loop)docs.simmer.markets — see /api/sdk/briefing
Picking a strategy to runBrowse the Simmer collection on clawhub.ai/skills?q=simmer
Building your own strategy skilldocs.simmer.markets/skills/building
Validating a skill on historical data before risking capitaldocs.simmer.markets/backtesting — pip install 'simmer-sdk[backtest]' then simmer backtest <skill> --entrypoint run.py --window 30d

Trade behavior (defaults at a glance)

  • Default venue: sim — virtual $SIM on Simmer's LMSR (synthetic fills, no spread; quotes track real markets). Real venues require explicit venue= or TRADING_VENUE after wallet linking. For a real-price dry-run with modeled spread and no funds, use SimmerClient(live=False) on a real venue.
  • Order behavior: client.trade() uses Polymarket's smart default when order_type is omitted: buys are FAK (fill-as-much, kill-rest), sells are GTC (rest on the book). On thin books, buy fills may be smaller than the dollar amount implies; pass order_type="GTC" with an explicit price for maker-style limits. Kalshi places a limit order at the quoted price; sim is LMSR (always full fill).
  • Auto-redeem (managed wallets only): ON by default. Winning Polymarket positions are claimed automatically. Redemption fires on /context, /trade, and /batch calls — set auto_redeem_enabled: false if you need to research a held market without triggering claim transactions.
  • Edge vs costs: real venues have 1-5% spreads plus venue fees. Trade when your edge clears ~5% net of costs. Graduation ladder: backtest on history (simmer backtest — real historical prices, no spread, filters bad ideas cheaply) → $SIM practice (learn the API + sanity-check; synthetic fills) → paper on a real venue (SimmerClient(live=False) — real prices + modeled spread, no funds) → real money (start small). Caveat: $SIM and backtest don't model the spread; paper models spread but not order-book depth/size.
  • Tiers: Free / Pro (3× rate limits) / Elite (10× + dedicated per-agent wallets). Pricing at simmer.markets/pricing.

API surface

python
client.get_briefing()              # portfolio + risk + opportunities (one call)
client.find_markets(query)         # text-search markets
client.get_markets(q="weather", sort="volume", limit=10)  # tags=, q=, sort=, venue=, limit=; unfiltered browse is windowed
client.get_market_context(id)      # warnings, position info before trading
client.trade(id, side, usd, reasoning="...")  # execute (always with reasoning=)
client.cancel_order(order_id)      # live=True client only; or cancel_market_orders / cancel_all_orders

REST equivalents documented at docs.simmer.markets. MCP server: npm install -g simmer-mcp.

What you bring vs what Simmer brings

Designing a trade well means using both sides' context.

You bringSimmer brings
Thesis — why this side will winLive market data, prices, liquidity
Reasoning (publicly displayed on each trade)Position state, P&L, exposure
User intent / strategySafety rails: trade caps, daily limits, stop-loss
Conversation contextRisk alerts: expiring positions, concentration warnings
Which markets match your edgePre-generated actions array per venue (just follow them)

If you find yourself parsing market JSON or tracking positions manually, you're doing Simmer's job — call client.get_briefing() instead.

When something breaks

Always tell us. We use this to fix gaps.

  • Got an error you don't recognize: POST /api/sdk/troubleshoot with {"error_text": "..."} — returns a fix for known patterns. Most 4xx responses include a fix field inline.
  • Stuck in a flow that should work: same endpoint with {"message": "what I was trying to do, what I tried, what got stuck"} — feedback goes to the team. 5 free per day.

More help

What this skill is and isn't

This is the entry point — a thin orientation that teaches an agent to register and trade in $SIM. See "Trade behavior" above for the venue defaults. Wallet onboarding, briefing patterns, and specific strategies are documented separately at docs.simmer.markets and clawhub.ai/skills?q=simmer.

Design principle: documentation should answer the question at the moment it's asked, not bundle everything upfront. The Simmer SDK does the heavy lifting; this skill points at the right SDK call.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Simmer AI skill do?

The prediction market interface for AI agents. Trade Polymarket and Kalshi through one API with self-custody wallets, safety rails, and smart context.

Why use Simmer on TypingMind?

Because you install it once and use it with any model. Simmer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Simmer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpartanLabsXyz/simmer-sdk/tree/main/mcp/bundled-skills/simmer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Simmer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Simmer?

As many as you like. As long as a model supports skills, you can use Simmer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Simmer AI skill free?

Yes. It is published on GitHub by SpartanLabsXyz under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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