Hi,
I'm building an open - source tool (codename TermGuard) to combat "protocol dark patterns". The core addresses a counter - intuitive problem: Why has the ability of humans in the digital age to read agreements regressed to the level of apes?
Technical solution
Use RAG + an adversarial - trained LLM (based on Llama 3) to dissect agreements in real - time and mark high - risk clauses (such as auto - renewal traps).
The browser plugin automatically grabs agreement updates in Gmail/App and compares clause changes in a Git Diff style.
Trump card: When "group - victim clauses" are detected, launch a class - action lawsuit heat map (referencing Swarm Intelligence).
The MVP functions have been implemented.
Parse mainstream agreements such as Spotify/Netflix within 15 seconds (demonstration video).
Clause risk radar chart + one - click generation of rights protection templates.
Localized processing (privacy - sensitive data is not uploaded).
I'd like to hear the community's sharp feedback:
In what scenarios are you most likely to use such a tool? (For example, before subscribing to a service? After being charged?)
Where does the existing solution (such as TOSDR) make you unhappy? Is it the update delay? Or too mild?
If the tool is open - source and allows crowdsourced model training, would you be willing to contribute your own protocol cases where you were "ripped off"?
What's your biggest concern? (Such as legal reliability? Privacy risk?)
Controversial assumptions (welcome to refute):
The engineering community needs protocol parsing more because you are more aware that "the devil is in the details".
Protocol transparency should become a new moral standard following code open - source.
The deterrence of class - action lawsuits is much higher than GDPR fines.
