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Polymarket Dca Eval Trader

Organization
SpartanLabsXyz
polymarket-dca-eval-trader

Build and optionally execute a three-tranche Polymarket DCA plan with prop-firm-shaped evaluation envelope checks. Use when the user wants a Bubbles/Roya-style staged averaging template for one thesis, with paper mode by default and explicit live opt-in.

Overview

PublisherSpartanLabsXyz
Repositorysimmer-sdk
Skill namepolymarket-dca-eval-trader
Stars
56
Forks
18
Bundled files
4
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.

  • 4 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 Polymarket Dca Eval Trader 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/skills/polymarket-dca-eval-trader
  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/skills/polymarket-dca-eval-trader .claude/skills/polymarket-dca-eval-trader
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Polymarket Dca Eval Trader 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 Polymarket Dca Eval Trader 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 Polymarket Dca Eval Trader 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.

Polymarket DCA Eval Trader

Three-tranche Polymarket DCA template for a single selected thesis. It is modeled as a Bubbles/Roya-style staged averaging framework, not as a guarantee of passing any evaluation.

Read DISCLAIMER.md before connecting funds.

Safety Rails

  • Paper mode is the default. Real orders require --live.
  • Exactly 3 tranches are supported. This is intentional so sizing and risk checks stay inspectable.
  • Per-market and daily exposure caps are enforced before any live order.
  • SDK preflight runs before live trading.
  • Every journaled event includes source=sdk:polymarket-dca-eval-trader.
  • SDK risk monitors are attached only when market duration supports them. Short markets may resolve before monitor cadence can act.
  • Defaults are configurable, not a pass guarantee.
  • No claim is made that this passes Propr or any prop challenge. Partnership or marketing claims remain blocked on a separate Adrian decision.

Strategy Shape

The skill enters one thesis through exactly three averaging levels:

TrancheDefault triggerDefault weight
10.0% price displacement or 0h elapsed34%
22.5% adverse price displacement or 24h elapsed33%
35.0% adverse price displacement or 48h elapsed33%

Schedule format:

bash
SIMMER_DCA_EVAL_TRANCHE_SCHEDULE="0:0:0.34,2.5:24:0.33,5:48:0.33"

Each entry is:

text
displacement_pct:elapsed_hours:size_weight

A tranche is eligible when either its adverse price displacement or elapsed-time trigger fires.

Default SL/TP

The default stop-loss and take-profit thresholds follow the requested Roya/Bubbles reference shape:

KnobDefault
SIMMER_DCA_EVAL_STOP_LOSS_PCT2.5
SIMMER_DCA_EVAL_TAKE_PROFIT_PCT4.5

The thresholds are calculated from weighted average selected-token entry price. They are configurable defaults, not evidence that the strategy is profitable.

Eval Envelope

Before a live order, the skill reports whether the executable tranche size would remain inside:

ConstraintDefault
Profit target10%
Static drawdown6%
Daily drawdown3%

The envelope assumes a full loss on the proposed executable tranche. Passing the envelope only means the proposed size fits those constraints. It does not predict trade outcome, skill profitability, or prop challenge approval.

Quick Start

bash
# Paper plan only
python dca_eval_trader.py --market MARKET_ID --side yes --anchor-price 0.55

# Paper plan with current price and elapsed time
python dca_eval_trader.py --market MARKET_ID --side yes --anchor-price 0.55 --current-price 0.52 --elapsed-hours 25

# Live trading after reviewing the JSON plan
python dca_eval_trader.py --market MARKET_ID --side yes --anchor-price 0.55 --current-price 0.52 --elapsed-hours 25 --live

Configuration

Env varDefaultDescription
SIMMER_DCA_EVAL_TOTAL_BUDGET30Total intended cost across all 3 tranches
SIMMER_DCA_EVAL_PER_MARKET_CAP50Max exposure on one market
SIMMER_DCA_EVAL_DAILY_CAP100Max new exposure per UTC day
SIMMER_DCA_EVAL_TRANCHE_SCHEDULE0:0:0.34,2.5:24:0.33,5:48:0.33Three tranche rules
SIMMER_DCA_EVAL_STOP_LOSS_PCT2.5Stop-loss percent from average entry
SIMMER_DCA_EVAL_TAKE_PROFIT_PCT4.5Take-profit percent from average entry
SIMMER_DCA_EVAL_ACCOUNT_SIZE10000Eval-envelope account size
SIMMER_DCA_EVAL_TARGET_PCT10Profit target percentage
SIMMER_DCA_EVAL_STATIC_DRAWDOWN_PCT6Static drawdown percentage
SIMMER_DCA_EVAL_DAILY_DRAWDOWN_PCT3Daily drawdown percentage

Journal

Default journal path:

text
~/.simmer/polymarket-dca-eval-trader/journal.jsonl

The journal records paper plans and live trades so repeated runs can enforce daily cap usage.

When Not To Use

Do not use this skill for:

  • Multi-market baskets.
  • Martingale sizing.
  • Fast markets where monitors cannot act before resolution unless the position is sized as if no exit automation exists.
  • Any public claim that this passes a prop-firm challenge.

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 Polymarket Dca Eval Trader AI skill do?

Build and optionally execute a three-tranche Polymarket DCA plan with prop-firm-shaped evaluation envelope checks. Use when the user wants a Bubbles/Roya-style staged averaging template for one thesis, with paper mode by default and explicit live opt-in.

Why use Polymarket Dca Eval Trader on TypingMind?

Because you install it once and use it with any model. Polymarket Dca Eval Trader 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 Polymarket Dca Eval Trader in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpartanLabsXyz/simmer-sdk/tree/main/skills/polymarket-dca-eval-trader. 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 Polymarket Dca Eval Trader?

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 Polymarket Dca Eval Trader?

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

Is the Polymarket Dca Eval Trader 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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