Oracle3
Open-source trading engine and MCP server for prediction markets. Fee-aware no-arbitrage trading across related contracts, live on Kalshi, Polymarket and Solana or on paper.
22K gold rate — closely matched to real shop prices, compared with Tanishq's listed rate when reachable. See if today's price is high or low compared to recent weeks.
FinancePython · JavaScriptGitHub @gaurav-gandhi-2411OnlineOwner unconfirmed
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Free $0/month gold-price tracker for Indian retail (Tanishq 22K): live 3h scrape, honest flat-hold range (no fake predictions), phone alerts via ntfy, installable PWA. Cloudflare Worker + GitHub Actions + GitHub Pages.
Translation pending
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
Buying gold jewellery in India? This page tells you today's 22K gold rate, how fresh that number is, and whether today's price is cheap or expensive compared with the recent past — in plain language, for free, with no ads and no sign-up.
Open it: https://gaurav-gandhi-2411.github.io/gold-rate-tracker/ — works in any phone browser, and can be installed like an app (iPhone: Safari → Share → Add to Home Screen; Android: Chrome → Install app).
Screenshots of the live page. Numbers in them are real production data at capture time, not mocked.Read the full README ↗Buying gold jewellery in India? This page tells you today's 22K gold rate, how fresh that number is, and whether today's price is cheap or expensive compared with the recent past — in plain language, for free, with no ads and no sign-up.
Open it: https://gaurav-gandhi-2411.github.io/gold-rate-tracker/ — works in any phone browser, and can be installed like an app (iPhone: Safari → Share → Add to Home Screen; Android: Chrome → Install app).
Screenshots of the live page. Numbers in them are real production data at capture time, not mocked.
Want phone alerts when the price moves? They are available if you run your own copy of the project (free, via the ntfy app) — see For developers.
No prediction of where the price goes next. No "% chance it rises." No buy or sell advice.
That's deliberate, not an omission. Every week the project tests whether any model can call the next move better than the simple rule "gold usually goes up, so just guess up". So far none has, with enough evidence to trust it, so the page shows nothing rather than a guess dressed up as insight (ADR 019, ADR 020). Even if a model someday passes that test, it still cannot appear on the page without a separate, explicit human sign-off (ADR 036).
The latest weekly results, updated automatically:
| Question | Honest answer | Source |
|---|---|---|
| Can any model call tomorrow's direction? | No, at either timeframe tested. Next day: <!--METRIC:data/direction_baseline.json#horizons.h1.logistic_metrics.accuracy:pct1 | n=horizons.h1.n_test_folds |
| Does the price forecast beat "just use today's price"? | No. Naive flat-hold: ₹249/g avg error. Chronos-Bolt-Tiny: ₹292/g avg error — 17% worse, over 209 walk-forward folds (p≈0). So the page shows today's price as the headline, not a forecast. | data/backtest.json @ ad42160 |
| Is the headline's own "likely range" well-calibrated? | Not yet known either way. Since a July 2026 fix (ADR 022), it has contained the real price <!--METRIC:data/coverage_metrics.json#coverage:pct1 | n=n |
No server, no database, no paid API. A scheduled GitHub Actions job fetches the IBJA rate (and tries Tanishq), works out the calibrated estimate and range, and commits the results as small JSON files; GitHub Pages serves a static web app that reads them. It costs nothing to run.
flowchart TD
subgraph cron["check-price.yml — scheduled"]
A["IBJA fetch<br/>primary source"] --> C
B["Tanishq read<br/>opportunistic enrichment"] --> C
C["prices.json<br/>ibja_rates.parquet"]
end
C --> D["ml.inference<br/>today's price headline<br/>+ IBJA calibration"]
D --> E["forecast.json"]
E --> F["ntfy.sh alerts"]
E --> G["commit data JSON to master"]
G --> H["GitHub Pages<br/>static web app"]
H --> I(("Your phone"))
subgraph weekly["eval-direction.yml — weekly"]
J["feature store"] --> K["direction models"]
K --> L{{"beats 'always guess up'<br/>with significance?"}}
L -->|"no"| M["stays hidden<br/>(ADR 019)"]
end
style M fill:#3a2418,stroke:#c67a4b,color:#e8c8a8
style D fill:#2a2015,stroke:#d4932a,color:#f0d9a8
Run your own copy (fork, set your own ntfy topic, enable Pages), alert setup, and troubleshooting: see docs/RUNBOOK.md → Running your own copy. Operating this deployment (rollback, CI debugging, staleness response, scraper and runner ops): docs/RUNBOOK.md. System design: docs/ARCHITECTURE.md. Audit history: docs/SESSION_AUDIT_2026-08.md.
| Path | What |
|---|---|
index.html, app.js, service-worker.js | The web app (what users see) |
scraper/ | Tanishq read (Node; a plain-HTTP path is tried first but is blocked by Cloudflare — it has succeeded 0 of <!--METRIC:data/tanishq_scrape_success_rate.json#n:int |
ml/ | Inference, calibration, notifications, the direction-eval harness |
data/ | Committed price/forecast/eval JSON the web app reads |
.github/workflows/ | check-price.yml (scheduled data refresh), lint.yml, eval-direction.yml, weekly-backtest.yml, scraper-canary.yml |
docs/ | RUNBOOK, ARCHITECTURE, ADRs, CURRENT_STATE, DIRECTION_SIGNAL_STATUS |
Every number in this README is injected from data/*.json by scripts/inject_metrics.py and re-checked in CI (docs-freshness), so it can't silently go stale — never type one by hand.
Built and maintained with heavy use of Claude Code — architecture decisions, ADRs, the ML pipeline, the web app, and CI are all human-directed but substantially AI-implemented. Documented here rather than hidden: every non-trivial design choice has a linked ADR explaining the why, written and kept current regardless of who typed the diff.