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OpenClaw

simmer-skill-builder

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.

adlai880 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install adlai88/simmer-skill-builder

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/adlai88/simmer-skill-builder
Version
—
Commit
d7e2f9a384fe5791480326bd85d0a01dbce724b0
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# 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...

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