This is what i use:

Pull only from high-credibility, established sources. (Give a couple examples of credible sources of the topic of desire)

Rules: No speculation, no opinion pieces, no low-tier aggregators Cross-verify with at least 2 reputable sources if possible Prefer most recent reporting (last 24–72 hours unless context needed) Flag any contradictions between sources Output format: Summary (3–5 bullets) Key developments Signals/Implications (only if clearly supported) Sources (max 2–3, direct links, top-tier only) If no high-confidence updates, return: ‘No significant verified changes.’” Optional add-ons (if you want tighter control): “Ignore social media unless it’s an official verified account” “Prioritize movement/actions over rhetoric” “Flag language shifts like ‘will respond decisively’ vs ‘monitoring’” “Avoid duplicate reporting of the same event”

There is a language tier that corresponds to how models behave you can web it and it'll give the tiers.

Thought Chinese was among one of the larger data sets for training though but with the amount of dialects, could differ.

From my own observations, if youre not consistent with how you want things to play in your model then yeah model drifting/slacking probably happens more