tried to do financial sentiment analysis but kept hitting the same wall with FinBERT: "OPEC cuts production" scores negative. For crude oil it should be bullish — less supply means higher prices. Generic models don't know what phrases mean for a specific asset.

No existing dataset captured this systematically. Every financial sentiment project I found was either abandoned or producing generic polarity that was actively wrong for commodities and FX.

So I built swik — at first for myself, then I kept finding zero alternatives and thought this could interest other people. Many sentiment analysis projects out there are abandoned for this very reason: failure to produce meaningful, correct and reliable sentiment for a given asset-specific headline.

Then I thought: "build it and they will come." Now there it is — an open, community-maintained catalog of phrase inversions for 35+ assets (commodities, FX, indices, crypto). Each entry has the phrase, naive polarity, actual direction for that asset, and the economic reasoning behind it.

The inference API takes a headline + security symbol and returns direction, magnitude, relevance, and confidence — with the inversion catalog injected as context.

What's open:

• 267 inversion entries across 35 assets (CC BY 4.0, on GitHub) • Free API (100 req/day, no credit card) • Label queue to contribute corrections

Still very early — the catalog grows with contributions. Curious whether others have hit this problem and how they've handled it.

swik.io | catalog: github.com/polibert/sentimentwiki-catalog