{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_dishgen","slug":"dishgen","name":"DishGen","type":"product","url":"https://dishgen.com","page_url":"https://unfragile.ai/dishgen","categories":["text-writing"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_dishgen__cap_0","uri":"capability://text.generation.language.natural.language.recipe.generation.from.ingredient.constraints","name":"natural language recipe generation from ingredient constraints","description":"Accepts free-form natural language descriptions of available ingredients, dietary preferences, and cuisine preferences, then uses an LLM backbone to generate contextually relevant recipes that match those constraints. The system parses ingredient lists and dietary restrictions from unstructured text input rather than requiring structured form selection, enabling users to describe 'I have chicken, garlic, and need something keto' in conversational language and receive tailored recipe suggestions with ingredient quantities and preparation steps.","intents":["Generate a recipe quickly without browsing multiple recipe sites or filling out forms","Find recipes that match my specific dietary restrictions without manually filtering results","Discover meal ideas based on ingredients I already have at home","Get recipe suggestions that accommodate multiple dietary needs simultaneously"],"best_for":["Home cooks with specific dietary needs (vegan, keto, gluten-free, allergies) seeking faster discovery","Users with ingredient constraints who want to minimize food waste","People who find traditional recipe search interfaces tedious or overwhelming"],"limitations":["No validation that generated recipes are nutritionally accurate or tested — relies entirely on LLM output quality","Cannot guarantee ingredient availability or cost optimization across regions","Natural language parsing may misinterpret ambiguous ingredient descriptions or non-standard dietary terminology","No persistent recipe history or user preference learning across sessions in free tier"],"requires":["Internet connection for API calls to LLM backend","Modern web browser (Chrome, Firefox, Safari, Edge)","No API key or authentication required for free tier"],"input_types":["natural language text (ingredient lists, dietary preferences, cuisine types)","comma-separated ingredient lists","dietary restriction keywords (vegan, keto, gluten-free, etc.)"],"output_types":["structured recipe text (ingredients with quantities, preparation steps, cooking time)","recipe metadata (servings, difficulty level, estimated prep/cook time)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_1","uri":"capability://data.processing.analysis.dietary.restriction.and.allergen.filtering.with.multi.constraint.support","name":"dietary restriction and allergen filtering with multi-constraint support","description":"Implements a constraint-satisfaction layer that filters generated recipes against user-specified dietary restrictions (vegan, vegetarian, keto, paleo, gluten-free, dairy-free, nut-free, etc.) and allergen profiles. The system likely maintains a mapping of common ingredients to allergen categories and dietary classifications, then validates recipe outputs against these constraints before presenting them to users, ensuring generated recipes do not contain prohibited ingredients or violate dietary rules.","intents":["Generate recipes that respect multiple simultaneous dietary restrictions","Ensure recipes do not contain specific allergens I need to avoid","Find meal options that fit my dietary philosophy without manual ingredient checking","Quickly filter out recipes that violate my dietary needs"],"best_for":["Users with diagnosed food allergies or intolerances requiring strict avoidance","People following specific diets (vegan, keto, paleo) who want guaranteed compliance","Parents meal-planning for children with multiple dietary restrictions","Users managing autoimmune or digestive conditions with complex dietary needs"],"limitations":["Allergen database may not cover all regional ingredient variations or cross-contamination risks","LLM-generated recipes may contain hidden allergens in sauces, broths, or processed ingredients not explicitly listed","No integration with nutritional databases to verify macronutrient targets (e.g., actual carb counts for keto)","Cannot account for individual sensitivity levels — treats all allergens as binary (present/absent)","No support for ingredient substitution suggestions if a recipe violates constraints"],"requires":["User must explicitly specify dietary restrictions during recipe generation","Internet connection for LLM inference","No special software or plugins required"],"input_types":["dietary restriction keywords (vegan, keto, gluten-free, dairy-free, nut-free, etc.)","allergen lists (peanuts, shellfish, soy, etc.)","multi-constraint combinations"],"output_types":["filtered recipe suggestions (recipes guaranteed to match constraints)","constraint compliance metadata (which restrictions each recipe satisfies)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_2","uri":"capability://text.generation.language.cuisine.type.and.flavor.profile.customization","name":"cuisine-type and flavor-profile customization","description":"Allows users to specify desired cuisine types (Italian, Thai, Mexican, Indian, etc.) and flavor profiles (spicy, savory, sweet, umami-forward) as input constraints, which the LLM uses to generate recipes that match both the ingredient/dietary constraints AND the culinary preferences. The system likely embeds cuisine and flavor characteristics in the prompt context, enabling the LLM to generate culturally appropriate recipes or flavor combinations rather than generic meals.","intents":["Generate recipes from a specific cuisine type using available ingredients","Find recipes with a particular flavor profile (spicy, sweet, savory) that match my constraints","Explore new cuisines while respecting dietary restrictions","Get recipe variety by specifying different cuisine preferences across multiple generations"],"best_for":["Home cooks wanting to explore specific cuisines within dietary constraints","Users seeking meal variety without manually researching cuisine-specific recipes","People who want authentic flavor profiles but need dietary modifications"],"limitations":["LLM may generate inauthentic or culturally inaccurate recipes, especially for less common cuisines","No access to regional ingredient availability — may suggest ingredients difficult to source in user's location","Flavor profile descriptions are subjective; 'spicy' or 'umami-forward' may not match user expectations","No validation that suggested cuisines are actually achievable with available ingredients"],"requires":["User must specify cuisine type or flavor preference during recipe generation","Internet connection for LLM inference"],"input_types":["cuisine type keywords (Italian, Thai, Mexican, Indian, Japanese, etc.)","flavor profile descriptors (spicy, sweet, savory, umami, tangy, etc.)","cuisine + ingredient + dietary constraint combinations"],"output_types":["cuisine-specific recipes with culturally appropriate ingredients and techniques","flavor-matched recipe suggestions"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_3","uri":"capability://data.processing.analysis.ingredient.quantity.and.serving.size.scaling","name":"ingredient quantity and serving size scaling","description":"Generates recipes with explicit ingredient quantities and serving sizes, and likely supports scaling recipes up or down based on desired serving counts. The system maintains proportional relationships between ingredients during scaling, ensuring that recipes remain balanced when adjusted from 2 servings to 6 servings or vice versa. This is typically implemented through LLM-guided calculation or post-processing of generated recipes to adjust quantities while preserving flavor and texture ratios.","intents":["Get recipes with specific ingredient quantities, not just ingredient lists","Scale recipes to match the number of people I'm cooking for","Adjust recipe portions without manually recalculating ingredient amounts","Plan meals for specific serving sizes without guessing proportions"],"best_for":["Home cooks who want precise ingredient measurements for consistent results","Meal planners preparing for specific group sizes","Users unfamiliar with recipe scaling or unit conversions"],"limitations":["LLM-generated quantities may not be tested or verified for accuracy","Scaling assumes linear proportionality, which breaks down for some ingredients (e.g., salt, spices, leavening agents)","No unit conversion support — may generate quantities in unfamiliar measurement systems (grams vs cups)","Cannot account for equipment constraints (e.g., scaling a recipe beyond oven capacity)","No cost calculation or ingredient sourcing guidance for scaled quantities"],"requires":["User must specify desired serving size or number of people","Internet connection for LLM inference"],"input_types":["desired serving count (e.g., 'for 4 people', 'makes 6 servings')","original serving size from generated recipe"],"output_types":["scaled ingredient lists with adjusted quantities","serving size metadata (prep time, cook time, total servings)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_4","uri":"capability://text.generation.language.step.by.step.recipe.instruction.generation.with.cooking.guidance","name":"step-by-step recipe instruction generation with cooking guidance","description":"Generates detailed, sequential cooking instructions for each recipe, breaking down preparation into discrete steps with estimated timing for each phase (prep, cooking, resting). The system likely uses the LLM to structure instructions in a clear, beginner-friendly format with explicit guidance on techniques, temperature targets, and doneness indicators. Instructions are generated contextually based on the recipe type and user's implied skill level, potentially including warnings about common mistakes or critical steps.","intents":["Get clear, step-by-step cooking instructions without ambiguity","Understand cooking techniques and why specific steps matter","Know how long each phase of cooking takes for time management","Receive guidance on doneness indicators and temperature targets"],"best_for":["Novice home cooks who need detailed, beginner-friendly instructions","Users cooking unfamiliar cuisines or techniques for the first time","People who want to understand the 'why' behind cooking steps, not just the 'what'"],"limitations":["LLM-generated instructions may omit critical details or assume user knowledge","Timing estimates are generic and do not account for equipment differences (gas vs electric stove, oven calibration)","No visual guidance or video references — text-only instructions may be insufficient for complex techniques","Cannot provide real-time feedback or troubleshooting if a step goes wrong","No adaptation based on user's actual cooking speed or equipment"],"requires":["Internet connection for LLM inference","Ability to read and follow text instructions"],"input_types":["recipe ingredients and cuisine type","implicit user skill level (inferred from dietary/ingredient constraints or explicit input)"],"output_types":["structured cooking instructions (numbered steps with timing)","technique guidance and doneness indicators","equipment and temperature recommendations"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_5","uri":"capability://memory.knowledge.persistent.user.preference.learning.and.recipe.history","name":"persistent user preference learning and recipe history","description":"Tracks user interactions with generated recipes (views, saves, ratings, regenerations) to build a preference profile that influences future recipe generation. The system likely stores user dietary restrictions, cuisine preferences, and past recipe feedback in a user account or session, then uses this history to personalize subsequent recipe suggestions. This enables the LLM to generate recipes more aligned with user tastes over time, avoiding repeated suggestions of disliked recipes or cuisines.","intents":["Get increasingly personalized recipe suggestions based on my past preferences","Avoid seeing recipes I've already rejected or disliked","Build a saved recipe collection for future reference","Let the system learn my taste preferences without re-specifying them each time"],"best_for":["Regular users who want personalized recipe discovery over time","Users with complex or evolving dietary preferences that benefit from learning","People building a personal recipe collection for meal planning"],"limitations":["Free tier likely has no persistent storage — preferences reset between sessions","No cross-device synchronization in free tier — preferences do not carry over between devices","Learning algorithm is opaque — users cannot see or edit their preference profile","Cold-start problem: new users receive generic suggestions until enough preference data is collected","No explicit feedback mechanism — system must infer preferences from implicit signals (clicks, saves)","Privacy concerns: user dietary and preference data is stored on DishGen servers"],"requires":["User account or persistent session storage (likely requires sign-up for paid tier)","Internet connection for preference synchronization","Cookies or local storage enabled in browser"],"input_types":["user recipe interactions (views, saves, ratings, regenerations)","explicit dietary and cuisine preferences","implicit signals (time spent on recipe, click patterns)"],"output_types":["personalized recipe suggestions","saved recipe collection","user preference profile (visible in paid tier only)"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_6","uri":"capability://planning.reasoning.batch.recipe.generation.and.meal.plan.creation","name":"batch recipe generation and meal plan creation","description":"Generates multiple recipes in a single request to support meal planning workflows, allowing users to request 'recipes for a week of dinners' or 'lunch ideas for 5 days' with specified dietary constraints and cuisine variety. The system likely maintains recipe diversity constraints to avoid suggesting the same ingredient or cuisine repeatedly, and may optimize for ingredient overlap to reduce shopping list complexity. This is implemented through multi-turn LLM prompting or batch processing that generates multiple recipes while enforcing diversity and ingredient efficiency rules.","intents":["Plan meals for multiple days without generating recipes one at a time","Get recipe variety while minimizing ingredient overlap for efficient shopping","Create balanced meal plans that respect dietary constraints across multiple days","Reduce meal planning time by generating a week's worth of recipes at once"],"best_for":["Meal planners preparing weekly or monthly menus","Budget-conscious users wanting to optimize ingredient overlap","Families with multiple dietary restrictions needing coordinated meal plans"],"limitations":["Batch generation may not optimize for ingredient cost or availability across recipes","No integration with grocery delivery or shopping list services","Diversity constraints may be weak — system may suggest similar recipes despite intent to vary","No nutritional balance checking across meal plan (e.g., ensuring adequate protein/vegetables daily)","Cannot account for ingredient seasonality or regional availability","Batch generation likely requires paid tier — free tier may limit to single-recipe generation"],"requires":["Specification of meal plan duration (e.g., '7 dinners', '5 lunches')","Dietary constraints and cuisine preferences for entire meal plan","Internet connection for batch LLM processing"],"input_types":["meal plan duration (number of days/meals)","dietary constraints and cuisine preferences","optional ingredient overlap preferences"],"output_types":["multiple recipes with consolidated shopping list","meal plan calendar with recipes assigned to specific days","ingredient overlap analysis (which recipes share ingredients)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_7","uri":"capability://text.generation.language.ingredient.substitution.and.adaptation.suggestions","name":"ingredient substitution and adaptation suggestions","description":"Provides alternative ingredient suggestions when a recipe contains ingredients the user cannot access, does not have on hand, or wants to replace for dietary or taste reasons. The system likely uses the LLM to understand ingredient functions (binder, thickener, acid, fat, protein) and suggests substitutes that maintain recipe balance and flavor. This enables users to adapt recipes to their constraints without requiring manual research or trial-and-error ingredient swapping.","intents":["Find substitutes for ingredients I don't have or can't access","Adapt recipes to use ingredients I prefer or have on hand","Replace ingredients due to allergies or dietary restrictions","Understand why a substitution works and how it affects the recipe"],"best_for":["Users with limited ingredient access or regional availability constraints","Home cooks wanting to adapt recipes to available ingredients","People managing allergies or dietary restrictions who need flexible recipe adaptation"],"limitations":["Substitution suggestions are not tested — may result in texture or flavor changes","LLM may not understand ingredient functions deeply enough for complex recipes (e.g., egg substitutes in baking)","No cost comparison between original and substitute ingredients","Cannot account for regional ingredient availability or pricing","Substitutions may violate dietary constraints if not carefully validated","No feedback mechanism to improve substitution quality based on user results"],"requires":["User must identify specific ingredient to substitute","Internet connection for LLM inference"],"input_types":["ingredient to replace","reason for substitution (allergy, unavailability, preference)","dietary constraints for substitute"],"output_types":["alternative ingredient suggestions with quantities","explanation of why substitution works","potential flavor or texture changes from substitution"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dishgen__cap_8","uri":"capability://data.processing.analysis.nutritional.information.estimation.and.macro.tracking","name":"nutritional information estimation and macro tracking","description":"Estimates nutritional content (calories, macronutrients, micronutrients) for generated recipes based on ingredient lists and quantities. The system likely integrates with a nutritional database (USDA, MyFitnessPal API, or similar) to look up ingredient nutrition facts, then aggregates them to provide per-serving nutritional breakdowns. This enables users to track macronutrients for specific diets (keto, high-protein) or manage caloric intake without manual calculation.","intents":["Know the calorie and macronutrient content of recipes before cooking","Track macronutrients for specific diets (keto, high-protein, low-carb)","Ensure recipes meet nutritional targets (e.g., minimum protein per serving)","Make informed decisions about recipe selection based on nutritional content"],"best_for":["Users following specific macronutrient-focused diets (keto, high-protein, low-carb)","Fitness enthusiasts tracking calories and macros for performance goals","People managing medical conditions requiring specific nutritional targets"],"limitations":["Nutritional estimates are approximations — actual values depend on specific ingredient brands and preparation methods","Database may not include all regional or specialty ingredients, leading to missing or inaccurate data","No account for cooking losses (water evaporation, fat rendering) that affect final nutritional content","Micronutrient tracking is often incomplete or inaccurate in public nutritional databases","No integration with fitness tracking apps (MyFitnessPal, Cronometer) for seamless macro tracking","Nutritional information likely requires paid tier — free tier may not include this feature"],"requires":["Access to nutritional database (USDA FoodData Central, MyFitnessPal API, or similar)","Accurate ingredient quantities in recipe","Internet connection for database queries"],"input_types":["recipe ingredients with quantities","serving size"],"output_types":["per-serving nutritional breakdown (calories, protein, carbs, fat, fiber)","macronutrient percentages","micronutrient estimates (vitamins, minerals)"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["Internet connection for API calls to LLM backend","Modern web browser (Chrome, Firefox, Safari, Edge)","No API key or authentication required for free tier","User must explicitly specify dietary restrictions during recipe generation","Internet connection for LLM inference","No special software or plugins required","User must specify cuisine type or flavor preference during recipe generation","User must specify desired serving size or number of people","Ability to read and follow text instructions","User account or persistent session storage (likely requires sign-up for paid tier)"],"failure_modes":["No validation that generated recipes are nutritionally accurate or tested — relies entirely on LLM output quality","Cannot guarantee ingredient availability or cost optimization across regions","Natural language parsing may misinterpret ambiguous ingredient descriptions or non-standard dietary terminology","No persistent recipe history or user preference learning across sessions in free tier","Allergen database may not cover all regional ingredient variations or cross-contamination risks","LLM-generated recipes may contain hidden allergens in sauces, broths, or processed ingredients not explicitly listed","No integration with nutritional databases to verify macronutrient targets (e.g., actual carb counts for keto)","Cannot account for individual sensitivity levels — treats all allergens as binary (present/absent)","No support for ingredient substitution suggestions if a recipe violates constraints","LLM may generate inauthentic or culturally inaccurate recipes, especially for less common cuisines","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.7300000000000001,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:30.283Z","last_scraped_at":"2026-04-05T13:23:42.552Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=dishgen","compare_url":"https://unfragile.ai/compare?artifact=dishgen"}},"signature":"k6Q259kTvpCnfLC0vvoOfLpXLEnI++HolxM9HWQgnMREQsmGm6x8eDyYrdn3/5PxTTCKyIsXavSmmMqLRgP+Bw==","signedAt":"2026-06-21T20:54:16.645Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/dishgen","artifact":"https://unfragile.ai/dishgen","verify":"https://unfragile.ai/api/v1/verify?slug=dishgen","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}