I built "w-bonkers": an agent-installable pipeline that runs my NSE stock plan on rails. My todo app is the approval button.
Every AI trading tool I tried had the same disease: ask it twice, get two different opinions. So I built the opposite - w-bonkers, a deterministic plan-refresh engine for Claude Code (works on Codex too). Same state + same pinned inputs + same rules = same output, every run.
- state.json is the single source of truth. The agent edits state; a Python script deterministically renders the action board, tasks, calendar, and Todoist payload. Views are never hand-edited.
- Todoist is the feedback bus. I comment "bought at 332" → next run records the fill, replies "✓ applied", never re-processes it. Ticking a BUY task means filled on the exchange, not "placed".
- Live broker data via Groww MCP, yfinance fallback. Prices are never invented.
- Deterministic rules: stop/trend/news exits, a regime gate that defers all new buys under the 200-DMA (backtested — harness is in the repo), and portfolio brakes (open-risk cap, weekly loss budget, a circuit breaker that files a p1 task instead of panic-selling).
- Every run archived to disk — fully auditable offline.
The agent never places a trade. It installs itself: clone, open Claude Code, say "read prompt.md" and it interviews you to build your plan.
Repo (MIT): https://github.com/Somchandra17/w-bonkers - educational tooling, not investment advice.
u/Somchandra17 — 9 hours ago