Twitter Cadence Model Trader

This is a template.
The default signal is a Poisson model based on historical posting rates — remix it with Twitter/X API v2 real-time post counts, time-of-day distributions, or NLP topic-burst detection.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Post-count bin markets (e.g., "Will Elon Musk post 190-214 tweets from March 30 to April 1?") are perfect for statistical modeling because the number of posts in a time interval follows a Poisson distribution.

Retail traders price these bins by gut feeling. This skill prices them with math.

Signal Logic

Poisson Model

Parse the person, bin range, and time period from the market question
Compute lambda = person's historical daily rate x period days
Calculate P(bin) = sum of Poisson PMF from bin_lower to bin_upper
Compare model probability to market price
Trade when model diverges from market AND price is in threshold band

Person Baselines

| Person | Daily Rate | Platform | |--------|-----------|----------| | Elon Musk | ~65 tweets/day | X/Twitter | | Donald Trump | ~23 posts/day | Truth Social | | Vitalik Buterin | ~8 posts/day | X/Twitter | | CZ | ~12 posts/day | X/Twitter |

Model Bias

The Poisson model acts as a conviction multiplier:

If model says bin is 2x more likely than market → 2x conviction boost
If model says bin is 0.5x less likely → signal vetoed (don't trade against math)

Remix Ideas

Twitter API v2: Replace baseline daily_rate with real-time 7-day rolling average
Time-of-day model: Elon posts 60% of tweets between 6PM-2AM Pacific — use hourly Poisson
Negative binomial: Better than Poisson for overdispersed counts (bursty posters)
Topic burst NLP: Detect thread-mode (3x rate) vs normal mode

Risk Parameters

| Parameter | Default | Notes | |-----------|---------|-------| | Max position size | $40 USDC | Per market | | Min market volume | $1,000 | Standard filter | | Max bid-ask spread | 10% | Default threshold | | Min days to resolution | 0 | Post-count markets are short-lived | | Max open positions | 8 | Diversify across bins |

Installation & Setup

clawhub install polymarket-twitter-cadence-model-trader

Requires: SIMMER_API_KEY environment variable.

Cron Schedule

Cron is set to null — the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.

| Scenario | Mode | Financial risk | |----------|------|----------------| | python trader.py | Paper (sim) | None | | Cron / automaton | Paper (sim) | None | | python trader.py --live | Live (polymarket) | Real USDC |

The automaton cron is set to null — it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.

Required Credentials

| Variable | Required | Notes | |----------|----------|-------| | SIMMER_API_KEY | Yes | Trading authority — keep this credential private. Do not place a live-capable key in any environment where automated code could call --live. |

Tunables (Risk Parameters)

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes. They use SIMMER_-prefixed env vars so apply_skill_config() can load them securely.

| Variable | Default | Purpose | |----------|---------|---------| | SIMMER_MAX_POSITION | 40 | Max USDC per trade (reached at 100% conviction) | | SIMMER_MIN_VOLUME | 1000 | Min market volume filter (USD) | | SIMMER_MAX_SPREAD | 0.10 | Max bid-ask spread (0.10 = 10%) | | SIMMER_MIN_DAYS | 0 | Min days until market resolves | | SIMMER_MAX_POSITIONS | 8 | Max concurrent open positions | | SIMMER_YES_THRESHOLD | 0.38 | Buy YES if market price ≤ this value | | SIMMER_NO_THRESHOLD | 0.62 | Sell NO if market price ≥ this value | | SIMMER_MIN_TRADE | 5 | Floor for any trade (min USDC regardless of conviction) |

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

PyPI: https://pypi.org/project/simmer-sdk/
GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
Publisher: hello@simmer.markets

Review the source before providing live credentials if you require full auditability.