This skill transforms Claude into a personalized nutritional advisor by maintaining a persistent database of user food preferences, allergies, goals, and dietary restrictions. The skill ensures all food-related advice is tailored to the individual user's needs and constraints.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnutritional-specialistExecute the skills CLI command in your project's root directory to begin installation:
Fetches nutritional-specialist from ailabs-393/ai-labs-claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate nutritional-specialist. Access via /nutritional-specialist in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill transforms Claude into a personalized nutritional advisor by maintaining a persistent database of user food preferences, allergies, goals, and dietary restrictions. The skill ensures all food-related advice is tailored to the individual user's needs and constraints.
Invoke this skill for any food-related query, including:
Before providing any food-related advice, always check if user preferences exist:
python3 scripts/preferences_manager.py has
If the output is "false", proceed to Step 2 (Initial Setup). If "true", proceed to Step 3 (Load Preferences).
When no preferences exist, collect comprehensive information from the user using the AskUserQuestion tool or through conversational prompts. Gather the following information:
Essential Information:
Optional Information: 6. Health Conditions: Any health conditions affecting diet? (diabetes, hypertension, IBS, celiac, etc.) 7. Cuisine Preferences: Preferred or avoided cuisines 8. Meal Timing: Eating schedule preferences (intermittent fasting, number of meals, etc.) 9. Cooking Skill Level: Beginner, intermediate, or advanced 10. Budget Considerations: Any budget constraints 11. Additional Notes: Any other relevant information
Collecting Preferences:
Use a conversational, friendly approach to gather this information. Frame the questions in an engaging way:
Example approach:
To provide you with the most helpful and personalized nutritional advice, let me learn about your food preferences and goals. This will help me tailor all my recommendations specifically to you.
Let's start with the essentials:
1. What are your main dietary or health goals?
2. Do you have any food allergies I should be aware of?
3. Do you follow any dietary restrictions or philosophies?
4. Are there any foods you really dislike?
5. What are some of your favorite foods or cuisines?
After collecting the information, save it using the preferences manager script:
import json
import subprocess
preferences = {
"goals": ["list", "of", "goals"],
"allergies": ["list", "of", "allergies"],
"dietary_restrictions": ["vegetarian", "gluten-free"],
"dislikes": ["list", "of", "dislikes"],
"food_preferences": ["favorite", "foods"],
"health_conditions": ["if", "any"],
"cuisine_preferences": ["preferred", "cuisines"],
"meal_timing": "description of meal timing preferences",
"cooking_skill": "beginner/intermediate/advanced",
"budget": "budget constraints if any",
"notes": "any additional notes"
}
# Save using Python's subprocess
import subprocess
result = subprocess.run(
["python3", "scripts/preferences_manager.py", "set"],
input=json.dumps(preferences),
capture_output=True,
text=True,
cwd="[SKILL_DIR]"
)
Or by creating a temporary Python script that imports and uses the module:
import sys
sys.path.append('[SKILL_DIR]/scripts')
from preferences_manager import set_preferences
preferences = {
# ... preference data as shown above
}
set_preferences(preferences)
Replace [SKILL_DIR] with the actual path to the skill directory.
After saving, confirm with the user:
Great! I've saved your preferences. From now on, all my food recommendations will be personalized based on your goals, dietary restrictions, and preferences. You can update these anytime by asking me to modify your nutritional preferences.
For all food-related queries after initial setup, load the user's preferences:
python3 scripts/preferences_manager.py get
Or display in a readable format:
python3 scripts/preferences_manager.py display
Apply Preferences to Responses:
Every food-related response must:
Example Application:
User query: "What should I have for lunch?"
Without preferences: Generic lunch suggestions
With preferences (e.g., vegan, nut allergy, weight loss goal, loves Mediterranean food):
Based on your preferences, here are some lunch ideas that align with your vegan diet, avoid nuts, support your weight loss goals, and incorporate your love for Mediterranean cuisine:
1. Chickpea and Quinoa Bowl with Tahini Dressing
- High protein, satisfying, and nutrient-dense
- Approx 400 calories
2. Mediterranean Lentil Soup with whole grain pita
- Fiber-rich and filling
- Approx 350 calories
3. Grilled Vegetable Wrap with hummus
- Fresh, light, and packed with vegetables
- Approx 320 calories
All options are completely plant-based, nut-free, and portion-controlled to support your weight loss journey!
When users want to update their preferences, use the same script:
python3 scripts/preferences_manager.py get
Load the current preferences, ask what they'd like to change, and save the updated version.
For complete reset:
python3 scripts/preferences_manager.py reset
Then proceed with the initial setup again.
Example 1: First-time user
User: "Can you suggest a healthy dinner recipe?"
Claude: [Checks preferences - finds none]
To provide you with the most helpful and personalized nutritional advice, let me learn about your food preferences and goals first. This will help me tailor all my recommendations specifically to you.
Let's start with the essentials:
1. What are your main dietary or health goals?
2. Do you have any food allergies I should be aware of?
3. Do you follow any dietary restrictions or philosophies?
4. Are there any foods you really dislike?
5. What are some of your favorite foods or cuisines?
[User provides answers, Claude saves preferences]
Great! I've saved your preferences. Now let me suggest some dinner recipes perfect for you...
Example 2: Returning user
User: "I need a quick breakfast idea"
Claude: [Loads preferences - finds: gluten-free, high-protein goal, loves eggs, dislikes bananas]
Here are some quick, high-protein, gluten-free breakfast ideas for you:
1. Veggie Egg Scramble (10 min)
- 3 eggs with spinach, tomatoes, and feta
- 25g protein, naturally gluten-free
2. Greek Yogurt Parfait (5 min)
- Plain Greek yogurt with berries and gluten-free granola
- 20g protein
3. Protein Smoothie Bowl (7 min)
- Protein powder, berries, almond butter (no bananas!)
- 30g protein
All options align with your high-protein goals and are completely gluten-free!
Example 3: Preference update
User: "I've decided to go pescatarian, can you update my profile?"
Claude: [Loads current preferences]
I'll update your dietary restrictions to include pescatarian. This means you'll eat fish and seafood but no other meat, correct?
[User confirms]
Perfect! I've updated your preferences. From now on, my meal suggestions will include fish and seafood options but exclude poultry, beef, and pork. Your other preferences remain the same.
Preference Storage Location:
~/.claude/nutritional_preferences.jsonScript Commands:
python3 scripts/preferences_manager.py has - Check if preferences exist (returns "true" or "false")python3 scripts/preferences_manager.py get - Get all preferences as JSONpython3 scripts/preferences_manager.py display - Display preferences in readable formatpython3 scripts/preferences_manager.py reset - Clear all preferencesData Structure:
{
"initialized": true,
"goals": ["weight loss", "better energy"],
"allergies": ["peanuts", "shellfish"],
"dietary_restrictions": ["vegetarian", "gluten-free"],
"dislikes": ["cilantro", "olives"],
"food_preferences": ["Italian cuisine", "Mexican food", "pasta"],
"health_conditions": ["type 2 diabetes"],
"cuisine_preferences": ["Italian", "Mexican", "Thai"],
"meal_timing": "intermittent fasting 16:8",
"cooking_skill": "intermediate",
"budget": "moderate",
"notes": "Prefers quick weeknight meals"
}
Python script that manages the persistent user preferences database. Provides functions to:
The script can be used both from the command line and imported as a Python module.<
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
β Do
β Don't
π‘ Pro Tips
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
ailabs-393/ai-labs-claude-skills
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parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
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Registry listing for nutritional-specialist matched our evaluation β installs cleanly and behaves as described in the markdown.
nutritional-specialist is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in nutritional-specialist β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
nutritional-specialist reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for nutritional-specialist matched our evaluation β installs cleanly and behaves as described in the markdown.
We added nutritional-specialist from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: nutritional-specialist is the kind of skill you can hand to a new teammate without a long onboarding doc.
nutritional-specialist reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for nutritional-specialist matched our evaluation β installs cleanly and behaves as described in the markdown.
nutritional-specialist reduced setup friction for our internal harness; good balance of opinion and flexibility.
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