simmer-skill-builder

name	simmer-skill-builder
displayName	Simmer Skill Builder
description	Generate complete, installable OpenClaw trading skills from natural language strategy descriptions. Use when your human wants to create a new trading strategy, build a bot, generate a skill, automate a trade idea, turn a tweet into a strategy, or asks "build me a skill that...". Produces a full skill folder (SKILL.md + Python script + config) ready to install and run.
metadata	{"clawdbot":{"emoji":"🛠️","requires":{"env":["SIMMER_API_KEY"],"pip":["simmer-sdk"]},"cron":null,"autostart":false,"automaton":{"managed":false,"entrypoint":null}}}
authors	["Simmer (@simmer_markets)"]
version	1.0.2
published	true

Simmer Skill Builder

Generate complete, runnable Simmer trading skills from a strategy description.

You are building an OpenClaw skill that trades prediction markets through the Simmer SDK. The skill you generate will be installed into your skill library and run by you — it must be a complete, self-contained folder that works out of the box.

Workflow

Step 1: Understand the Strategy

Ask your human what their strategy does. They might:

• Describe a trading thesis in plain language
• Paste a tweet or thread about a strategy
• Reference an external data source (Synth, NOAA, Binance, RSS, etc.)
• Say something like "build me a bot that buys weather markets" or "create a skill for crypto momentum"

Clarify until you understand:

1. Signal — What data drives the decision? (external API, market price, on-chain data, timing, etc.)
2. Entry logic — When to buy? (price threshold, signal divergence, timing window, etc.)
3. Exit logic — When to sell? (take profit threshold, time-based, signal reversal, or rely on auto-risk monitors)
4. Market selection — Which markets? (by tag, keyword, category, or discovery logic)
5. Position sizing — Fixed amount or smart sizing? What default max per trade?

Step 2: Load References

Read these files to understand the patterns:

1. references/skill-template.md — The canonical skill skeleton. Copy the boilerplate blocks verbatim (config system, get_client, safeguards, execute_trade, CLI args).
2. references/simmer-api.md — Simmer SDK API surface. All available methods, field names, return types.

If the Simmer MCP server is available (simmer://docs/skill-reference resource), prefer reading that for the most up-to-date API docs. Otherwise use references/simmer-api.md.

For real examples of working skills, read:

• references/example-weather-trader.md — Pattern: external API signal + Simmer SDK trading
• references/example-mert-sniper.md — Pattern: Simmer API only, filter-and-trade

Step 3: Get External API Docs (If Needed)

If the strategy uses an external data source:

• Polymarket CLOB data: If the Polymarket MCP server is available, search it for relevant endpoints (orderbook, prices, spreads). If not available, the key public endpoints are:
  • GET https://clob.polymarket.com/book?token_id=<token_id> — orderbook
  • GET https://clob.polymarket.com/midpoint?token_id=<token_id> — midpoint price
  • GET https://clob.polymarket.com/prices-history?market=<token_id>&interval=1w&fidelity=60 — price history
  • Get polymarket_token_id from the Simmer market response.
• Other APIs (Synth, NOAA, Binance, RSS, etc.): Ask your human to provide the relevant API docs, or web-fetch them if you have access.

Step 4: Generate the Skill

Create a complete folder on disk:

<skill-slug>/
├── SKILL.md          # Metadata + documentation
├── <script>.py       # Main trading script
└── scripts/
    └── status.py     # Portfolio viewer (copy from references)

SKILL.md Requirements

• YAML frontmatter with name, displayName, description, metadata (including automaton entrypoint), version: "1.0.0", published: true
• requires.pip must include simmer-sdk
• requires.env must include SIMMER_API_KEY
• Body must include: "This is a template" callout, setup flow, configuration table, quick commands, example output, troubleshooting section

Python Script Requirements

Copy these verbatim from references/skill-template.md:

• Config system (_load_config, _get_config_path, _update_config)
• get_client() singleton
• check_context_safeguards()
• execute_trade()
• calculate_position_size()
• CLI entry point with standard args (--live, --positions, --config, --set, --smart-sizing, --no-safeguards, --quiet)

Customize:

• CONFIG_SCHEMA — skill-specific params with SIMMER_<SKILLNAME>_<PARAM> env vars
• TRADE_SOURCE — unique tag like "sdk:<skillname>"
• Signal logic — your human's strategy
• Market fetching/filtering — how to find relevant markets
• Main strategy function — the core loop

Step 5: Validate

Run the validator against the generated skill:

python /path/to/simmer-skill-builder/scripts/validate_skill.py /path/to/generated-skill/

Fix any FAIL results before delivering to your human.

Hard Rules

1. Always use SimmerClient for trades. Never import py_clob_client, polymarket, or call the CLOB API directly for order placement. Simmer handles wallet signing, safety rails, and trade tracking.
2. Always default to dry-run. The --live flag must be explicitly passed for real trades.
3. Always tag trades with source=TRADE_SOURCE (e.g. "sdk:synth-volatility").
4. Always include safeguards — the check_context_safeguards() function, skippable with --no-safeguards.
5. Always include reasoning in execute_trade() — it's displayed publicly and builds your reputation.
6. Use stdlib only for HTTP (urllib). Don't add requests, httpx, or aiohttp as dependencies unless your human specifically needs them. The only pip dependency should be simmer-sdk.
7. Polymarket minimums: 5 shares per order, $0.01 min tick. Always check before trading.
8. Include sys.stdout.reconfigure(line_buffering=True) — required for cron/Docker/OpenClaw visibility.
9. get_positions() returns dataclasses — always convert with from dataclasses import asdict.
10. Never expose API keys in generated code. Always read from SIMMER_API_KEY env var via get_client().

Naming Convention

• Skill slug: polymarket-<strategy> for Polymarket-specific, simmer-<strategy> for platform-agnostic
• Trade source: sdk:<shortname> (e.g. sdk:synthvol, sdk:rssniper, sdk:momentum)
• Env vars: SIMMER_<SHORTNAME>_<PARAM> (e.g. SIMMER_SYNTHVOL_ENTRY)
• Script name: <descriptive_name>.py (e.g. synth_volatility.py, rss_sniper.py)

Example: Tweet to Skill

Your human pastes:

"Build a bot that uses Synth volatility forecasts to trade Polymarket crypto hourly contracts. Buy YES when Synth probability > market price by 7%+ and Kelly size based on edge."

You would:

1. Understand: Signal = Synth API probability vs Polymarket price. Entry = 7% divergence. Sizing = Kelly. Markets = crypto hourly contracts.
2. Read references/skill-template.md for the skeleton.
3. Read references/simmer-api.md for SDK methods.
4. Read references/example-weather-trader.md — closest pattern (external API signal).
5. Ask your human for Synth API docs or web-fetch them.
6. Generate polymarket-synth-volatility/ with:
   • SKILL.md (setup, config table, commands)
   • synth_volatility.py (fetch Synth forecast, compare to market price, Kelly size, trade)
   • scripts/status.py (copied)
7. Validate with scripts/validate_skill.py.