Phil — AI skill for Claude Code
Phil is a self-improving trader: an AI agent that trades short-term prediction markets and rewrites his own strategy after every settled bet.
How to install Phil
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open bennyjo/phil and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Phil does
Phil is a self-improving trader: an AI agent that trades short-term prediction markets and rewrites his own strategy after every settled bet. Paper 24/7 in the cloud; small capped real stakes via Pearl Connect.
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README
Phil the self-improving trader
[](https://github.com/bennyjo/phil/actions/workflows/ci.yml)
**Phil is a self-improving trader: an AI agent that trades short-term prediction markets and rewrites its own strategy after every resolved bet.** Paper trading is the 24/7 learning engine. Real money runs alongside it, deliberately small: capped stakes through [Pearl Connect](https://github.com/valory-xyz/connect), only in edge classes whose settled evidence has earned it.
The name honors the man who relived the same day until he'd learned enough to win it, and the groundhog who makes forecasts.
The experiment
Claude Code gets a simulated $1,000 bankroll and the short-term Polymarket universe: earnings beats, daily sports, pre-match esports, official economic prints, near-term news. Crypto up-or-down coin-flips are banned. Every cycle it settles yesterday's bets against official resolutions and scores its own calibration against the market price it paid. It writes a retrospective when bets have settled. A swarm of cheap screening subagents scores ~300 markets per full cycle against the live price (`core/screen.py`), and the agent spends its research slots on the largest divergences. It **edits its own playbook, risk policy, tooling, sensing** (the market-discovery queries and the screening prompt) **and pacing** (which hourly ticks deserve a full cycle). Then it commits the diff, researches, and bets again.
Three layers keep it honest:
- an hourly cycle agent that screens, researches, bets, and self-edits,
plus lightweight watchers (
core/watch.py) that check every ~15 minutes for new listings and price moves on the agent's watchlist and trigger an early cycle when something fires; - a daily deep-retro agent that audits every strategy edit (keep, sharpen, or
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