Ruby Cot Erotic Massage ❤️❤️❤️❤️

Girls in Cot are ready for men to share lifes joy

Profile Photo
Location Cot, Costa Rica
Mistress ❤️❤️
OWO - Oral without condom ❤️
Golden Shower (give) for extra charge No
Titjob Maybe
Rimming (take) Not sure
Facesitting (give) for extra charge Rarely
Fingering Never
69 Position Partially
Cunnilingus (give) for extra charge Always
Bust size F
Bust type Saline
Orientation Questioning
Occupation Artist
Marital status Divorced
Height 164 cm
Weight 76 kg
Hair color Pink
Hair length Very long
Eyes color Green
Body type Plus-size
Religion Hindu
Ethnicity Indian
Education Trade School
Smoker Regular smoker
Array Social drinker
Level of english Fluent

About Myself

Yo, Ruby here, whats good?. I am entrenched in Cot, and the buzz about Erotic Massage wont stop? I am enchanted by your boundless spirit. I revere Mistress and OWO - Oral without condom, i am not interested in putting on a façade or hiding behind masks..

My address: Cot, Avenida Central Street, home 68* *** **

Phone: ( +506 ) 5257****

About Heredia

Eh, what’s up, doc? So, erotic-massage, huh? Man, it’s wild! Gets ya all tingly, right? Like, imagine this – hands slidin’ everywhere, oil drippin’, tension just meltin’ away. Kinda reminds me of *Requiem for a Dream* – ya know, that crazy vibe where it’s all intense and messy? “I’m somebody now, Harry!” – that’s me after a good rubdown, feelin’ alive!

What is Erotic Massage?

Oh, my friend, let me tell ya bout Cot (cr)! I live here, ya know, as a pleasure coach extraordinaire. Lightbulb! This city is just like Spring Breakers – wild, catchy and a bit insane, yes? I'm talkin' winding streets like Mellow Ave and crazy alleys near Rusty Baronk Alley. Yo, these streets got life, real life, ya feel me?

Advanced Prompt Engineering: Chain of Thought (CoT)

It facilitates problem-solving by guiding the model through a step-by-step reasoning process by using a coherent series of logical steps, prompt engineering is used in artificial intelligence to refine inputs (prompts) to get the most accurate model outputs. In this study, the concept of chain of thought prompting is introduced which elicits reasoning in LLMs.1 The paper argues that prompting models to generate intermediate reasoning steps significantly boosts their ability to accurately solve multistep problems like arithmetic.
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