food-science
Analyzes food science topics including nutritional composition, food chemistry, food safety hazard analysis, sensory evaluation design, and food processing…
Skill by beita6969
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/beita6969-food-science
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: design
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/food-science
What's inside
- Skill name
food-science- Description
- Analyzes food science topics including nutritional composition, food chemistry, food safety hazard analysis, sensory evaluation design, and food processing optimization; trigger when users discuss nutrients, food additives, HACCP, shelf life, or food product development.
- License
- MIT
- Instructions
- 49 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
## When to Trigger Activate this skill when the user mentions: - Nutritional analysis, macronutrients, micronutrients, dietary reference intakes - Food chemistry, Maillard reaction, emulsification, gelation - Food safety, HACCP, critical control points, pathogen analysis - Sensory evaluation, taste panels, hedonic scales - Food processing, pasteurization, fermentation, preservation - Shelf life, water activity, food packaging - Dietary assessment, food frequency questionnaire, 24-hour recall ## Step-by-Step Methodology 1. **Define the food science question** - Specify the food matrix (raw ingredient, processed product, meal). Identify whether the question is about composition, safety, processing, sensory properties, or health effects. 2. **Nutritional analysis** - Query food composition databases (USDA FoodData Central, EFSA). Report per serving and per 100g. Compare against DRIs (Dietary Reference Intakes) or RDAs. Account for bioavailability and cooking losses. 3. **Food chemistry analysis** - Identify key chemical reactions (Maillard browning, lipid oxidation, enzymatic browning, starch gelatinization). Characterize relevant physical chemistry (pH, water activity, emulsion stability, rheology). Relate to quality attributes (color, texture, flavor). 4. **Food safety assessment** - Identify hazards: biological (pathogens: Salmonella, Listeria, E. coli O157:H7), chemical (pesticides, mycotoxins, heavy metals, allergens), physical (foreign objects). Apply HACCP principles: hazard analysis, critical control points, critical limits, monitoring, corrective actions. 5. **Process optimization** - Define processing parameters (temperature, time, pH, pressure). Model thermal processing (D-value, z-value, F0 calculations for sterilization). Optimize for safety while minimizing quality loss. Consider novel technologies (HPP, PEF, UV). 6. **Sensory evaluation** - Design appropriate test: discrimination (triangle, duo-trio), descriptive (QDA, CATA), or affective (hedonic, preference). Determine panel size (trained vs. consumer), number of replicates, and serving conditions. Apply appropriate statistical analysis. 7. **Shelf life estimation** - Monitor quality indicators over time (microbial counts, chemical markers, sensory scores). Model degradation kinetics (zero or first order). Apply accelerated shelf life testing (ASLT) with Arrhenius equation for temperature-dependent reactions. ## Key Databases and Tools - **USDA FoodData Central** - US food composition database - **EFSA / Codex Alimentarius** - Food safety standards - **FDA Food Safety** - US food regulations - **CompTox (EPA)** - Chemical toxicity data - **Mintel / Innova Market Insights** - Food product trends ## Output Format - Nutritional composition tables: nutrient, amount per serving, % DRI. - HACCP plan as a table: hazard, CCP, critical limit, monitoring, corrective action. - Thermal processing: D-values, z-values, F0 calculation with target organism. - Sensory results: panel demographics, test statistics, significance levels. - Shelf life: degradation curves, estimated shelf life with confidence intervals. ## Quality Checklist - [ ] Food composition data source and version specified - [ ] Serving sizes clearly defined and consistent - [ ] HACCP analysis covers all three hazard categories (biological, chemical, physical) - [ ] Thermal processing targets the most resistant pathogen of concern - [ ] Sensory evaluation design includes proper controls and blinding - [ ] Regulatory framework identified (FDA, EFSA, Codex) - [ ] Allergen considerations addressed - [ ] Shelf life conditions (temperature, humidity, packaging) specified
From beita6969/ScienceClaw, MIT.
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Signals
- Stars
- 1,019
- Forks
- 109
- Open issues
- 1
- Last commit (this folder)
- Mar 12, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/beita6969/ScienceClaw
- Website
- scienceclaw.science
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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food-science skill. Agent Mart. https://agentmart.dev/skills/beita6969-food-science (last updated 2026-10-24)