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Weather & Lighting Image Commands
Transform a scene with rain, snow, natural light, practical sources, neon, silhouettes, and expressive shadows.
Testés · Adaptables · Par modèle
Explorez des prompts testés avec résultats réels, variables claires et notes pour les principaux modèles.
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Chaque carte montre ce que le prompt produit, pas seulement ce qu’il dit.
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Transform a scene with rain, snow, natural light, practical sources, neon, silhouettes, and expressive shadows.
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Create reflective, gravity-defying, scale-bending, abstract, and geometric scenes with controlled surreal logic.
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Apply fluid, crystalline, metallic, iridescent, luminous, particle, energy, and portal effects with material clarity.
Create distinct paid-social ad angles without repeating the same claim.
Turn a target query and business goal into a writer-ready search brief.
Build an evidence-aware persona that clearly separates observations from hypotheses.
Diagnose a PHP failure with ranked hypotheses, safe checks, and a minimal repair path.
Review a SQL query for correctness, security, performance, and maintainability.
Convert a business idea into assumptions, options, milestones, and stop conditions.
Transform messy meeting notes into decisions, owners, deadlines, and unresolved questions.
Analyze long source material without losing citation boundaries or unresolved conflicts.
Create a practical short-form UGC concept with hook, shots, dialogue, and production notes.
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Pourquoi ça marche
Nous séparons rôle, contexte, contraintes et format, puis notons modèles, date et échecs.
Méthode de testExemple pédagogique rédigé, pas une réponse de modèle enregistrée.
A worked meeting-note exercise with incomplete assignments, conflicting dates, a reference answer and a repeatable review checklist.
Exemple pédagogique rédigé, pas une réponse de modèle enregistrée.
Learn to separate supported facts, conflicts and unknowns using a small source packet instead of asking for an unsupported research verdict.
Exemple pédagogique rédigé, pas une réponse de modèle enregistrée.
A practical appointment-extraction example that separates syntax, schema, business rules and missing facts, including a local JSON exercise.