Social Trends & Wellbeing Trader

> This is a template.

> The default signal is keyword-based market discovery combined with conviction-based sizing and policy_bias() — remix it with the data sources listed below.

> The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Social policy markets are dominated by ideologically motivated traders who bet on what they want to happen, not what evidence suggests will happen. This is the most consistent and exploitable mispricing pattern on Polymarket. The skill corrects for it with two hard-coded structural edges: issue-type ideological distortion and the US legislative calendar.

Signal Logic

Default Signal: Conviction-Based Sizing with Policy Bias

1. Discover active social policy and wellbeing markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply policy_bias() — combines ideological motivation correction with legislative calendar
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAX_POSITION
5. Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution

Policy Bias (built-in, no API required)

Factor 1 — Ideological Motivation Correction

The dominant pricing force in social policy markets is not information — it is tribal loyalty. Each policy domain attracts a different ideological crowd, each systematically overpricing the outcome they want:

The Cannabis Rule deserves emphasis: federal cannabis legalization markets have resolved NO every single time since 1970. Retail prices them at 15–40% based on polling support, confusing public opinion with legislative probability. The federal base rate is near zero. Every federal cannabis legalization market is a structural NO.

Factor 2 — US Legislative Calendar

GovTrack documents that all US bills pass at ~3–5%. But this already-low rate varies sharply by calendar:

This calendar multiplier only applies to legislative markets ("will Congress pass X", "will Senate vote on Y"). FDA approvals, HUD data releases, and similar non-legislative markets are unaffected.

The skill prints election_gridlock=True/False on startup so you always know which regime you're in. (2026 is a US midterm year — gridlock mode activates August 2026.)

Combined Examples

Keywords Monitored

mental health, suicide rate, drug legalization, cannabis, psychedelics,
loneliness, social media ban, teen smartphone, TikTok ban, gun control,
marijuana, psilocybin, FDA mental health, universal basic income, UBI,
poverty rate, homelessness, opioid, fentanyl, drug decriminalization,
safe injection, gun violence, background check, red flag law,
assault weapon, SNAP, welfare, Medicaid expansion, healthcare access

Remix Signal Ideas

• GovTrack.us API: Bill stage progression (introduced → committee → floor) — committee advancement is the single strongest predictor of passage; feed bill stage into p to trade divergence from naive retail pricing
• SAMHSA drug survey data: Annual survey release dates for drug use and policy markets — data-release markets have known calendars retail ignores
• Gallup social trends polling: Long-run public opinion series for legalization and mental health — useful for calibrating YES_THRESHOLD per issue

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

autostart: false and cron: null — nothing runs automatically until you configure it in Simmer UI.

Required Credentials

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk