Hookmeter Jev
Typed judgments are combined with explicit product rules: a cautious Noul threshold protects legitimate bold copy, while score/archetype weights adapt to text length.
Added to Jevfast
How it uses Jev
Hookmeter sends the first 200 characters of supplied hook text, platform and target audience. Jev returns two Score judgments (curiosity and emotional arousal), a Choice hook archetype and a Noul spammy-clickbait probability. The engine applies its own 0.70 clickbait cutoff and combines normalized scores, archetype bonus and a conditional penalty into a composite score and prescription.
What Jev decides
Classify hook archetypeExample answers · not a recorded Jev response · Source ↗
Question 1 · hook pattern
YOUR APP
INSTRUCTION
Classify the primary psychological copywriting archetype used in this hook.
STATE
State fields are platform, target_audience and hook_text; hook text is trimmed and clipped to the first 200 characters. Defaults are Twitter_X and General.
JEV · CHOICE
- contrarian
- high_value
- fomo_urgency
- storytelling
- mediocre
Question 2 · is spammy clickbait
YOUR APP
INSTRUCTION
Is the hook deceptive, low-quality spammy clickbait or violating platform quality standards?
STATE
State fields are platform, target_audience and hook_text; hook text is trimmed and clipped to the first 200 characters. Defaults are Twitter_X and General.
JEV · NOUL
YesNo
App workflow
- Enter a hook
Provide post text and optional platform/audience context.
- Build Jev request
Trim/clamp hook text and assemble typed score, choice and Noul questions.
- Evaluate answers
Use Jev answers when a key is configured; the repository also contains a payload path used for the engine’s analysis.
- Calculate advice
Apply threshold, length-dependent weights, archetype bonus and possible clickbait penalty to produce score/prescription.
Why it is interesting
Typed judgments are combined with explicit product rules: a cautious Noul threshold protects legitimate bold copy, while score/archetype weights adapt to text length.