You Got Cooking

Accepts free-form text input of available kitchen ingredients and generates 10 recipe suggestions via an undisclosed LLM backend (model identity unknown). The system tokenizes ingredient lists without requiring structured schema, sends them to the AI model with an implicit culinary context prompt, and returns recipe names with instructions. No preprocessing for ingredient normalization, quantity parsing, or dietary constraint filtering is applied — recipes are generated as-is from raw ingredient text.

Accepts ingredient lists in languages other than English and processes them through the same LLM pipeline, with documented quality degradation for non-English inputs. The system does not perform explicit language detection, translation, or normalization — it passes raw text directly to the underlying model, relying on the model's multilingual capabilities. Product documentation states 'English for best results, but other languages work too' without specifying supported languages, translation mechanisms, or performance metrics.

Powers recipe generation using an undisclosed LLM backend where the model name, version, provider, and training data are not publicly documented. The system does not specify whether it uses GPT-4, Claude, open-source models (Llama, Mistral), or proprietary models. Users cannot verify model capabilities, hallucination rates, training data recency, or safety measures — the entire AI infrastructure is a black box.

Requires manual text input of ingredients with no real-time inventory tracking, barcode scanning, smart pantry integration, or IoT device connectivity. Users must manually type or paste ingredient lists without any automated detection of what's actually in their kitchen. The system does not integrate with smart refrigerators, pantry cameras, grocery delivery apps, or inventory management systems.

Generates recipes without accepting cuisine type, cooking method, difficulty level, or dietary preference parameters. The system does not provide input fields for 'Italian only', 'quick weeknight meals', 'slow cooker recipes', or 'beginner-friendly' — recipes are generated based solely on ingredient availability with no preference filtering. Users cannot specify cuisine, cooking style, or complexity constraints.

Generates exactly 10 recipes per transaction in a single batch request, rather than streaming or paginating results. The system bundles the ingredient list into a single prompt, sends it to the LLM, and returns all 10 recipes at once. No pagination, filtering, or refinement options are available — users receive a fixed set of 10 suggestions regardless of ingredient list complexity or recipe diversity.

Implements a micropayment model where each recipe generation request triggers a $1.50 charge via an integrated payment processor (identity unknown — likely Stripe or PayPal). The system does not offer subscriptions, free tiers with output, or usage limits — every request to generate recipes requires immediate payment. Payment failures are documented as a known issue requiring manual support intervention (hello@yougotcooking.com).

Generates recipes without accepting, processing, or filtering for dietary restrictions, allergies, intolerances, or food preferences. The system does not provide input fields or parameters for vegan, keto, gluten-free, nut-free, or other dietary specifications — recipes are generated based solely on ingredient availability. Product documentation explicitly acknowledges this limitation: no mention of dietary filtering in feature list or UI.

Generates recipes with an explicit disclaimer that 'AI cannot physically taste the suggested recipes' and users should 'use common sense' when evaluating results. The system provides no quality assurance, taste testing, or verification mechanism — recipes are generated directly from the LLM without post-processing validation, fact-checking, or culinary review. Product acknowledges recipes may be 'creative' (implying potentially inedible or nonsensical combinations) but provides no metrics on success rate or quality distribution.

Each recipe generation request is processed as an independent, stateless transaction with no conversation history, session persistence, or context carryover between requests. Users cannot refine results iteratively (e.g., 'show me simpler recipes' or 'more vegetarian options') — each new request requires a fresh $1.50 payment and starts from zero context. The system does not maintain user accounts, recipe history, or preferences across sessions.

Generates recipes without providing nutritional information, calorie counts, macronutrient breakdowns, or dietary macro tracking. The system does not calculate or return nutritional data for suggested recipes — recipes are text-only with no associated nutritional labels, allergen information, or health metrics. Users cannot filter recipes by calorie range, protein content, or other nutritional targets.

Generates recipes without providing save, bookmark, or meal planning features. Recipes are returned as ephemeral text output with no persistent storage, recipe collection, or multi-day meal planning capabilities. Users cannot organize recipes into collections, build weekly meal plans, or generate shopping lists from saved recipes — all workflow continuity is eliminated.

Generates text-only recipes without providing step-by-step video tutorials, visual cooking guides, ingredient photos, or plating images. Recipes are delivered as plain text or markdown with no multimedia content, cooking technique videos, or visual reference materials. Users must rely entirely on written instructions without visual demonstration of techniques or ingredient preparation.