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nutripulse

Provides global nutrition intelligence through endpoints for research synthesis, supplement analysis, personalized meal planning, food database lookups, glucose interpretation, and longevity protocols.

Instructions

NutriPulse: Global nutrition intelligence API. PubMed-grounded supplement analysis, macro/micronutrient planning, food database lookups, glucose/metabolic health guidance, lab result interpretation, longevity nut

Coverage: Global

Endpoints: • research ($0.10): Nutrition research synthesis • food ($0.08): Food nutrition profile • supplement ($0.10): Supplement analysis • plan ($0.15): Personalized nutrition plan • compare ($0.08): Food comparison • analyze ($0.08): Meal analysis • stack ($0.12): Supplement stack • glucose ($0.10): CGM glucose pattern interpretation • interactions ($0.10): Supplement interaction checker • labs ($0.15): Blood work interpretation • longevity ($0.10): Longevity protocol synthesis • prenatal ($0.10): Prenatal nutrition by trimester

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageNoAge
sexNoSex
dietNodiet
goalNogoal
langNolang
mealNomeal
nameNoname
foodsNoComma-separated food names e.g. chicken,beef,tofu
goalsNoHealth goals
queryNoquery
topicNotopic
actionYesWhich endpoint to call. Options: research | food | supplement | plan | compare | analyze | stack | glucose | interactions | labs | longevity | prenatal
budgetNobudget
contextNoAdditional context
markersNoComma-separated lab markers and values
patternNoGlucose pattern description or readings
caloriesNocalories
trimesterNoTrimester (1, 2, 3)
conditionsNoExisting conditions
medicationsNoComma-separated medications
supplementsNoComma-separated supplements
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. The description does not disclose behavioral traits such as data freshness, rate limits, error handling, or how parameters interact. Mentions 'PubMed-grounded' but no further details on sourcing or coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy, includes a bullet list with pricing, and has marketing language. It could be more concise and structured for quick consumption.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 21 parameters and 12 actions, the description provides an overview but lacks guidance on which parameters are needed for each action, expected output, or examples. No output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description repeats some parameter names in the endpoint list but does not add significant new meaning beyond the schema's descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the domain (global nutrition intelligence) and lists 12 specific endpoints covering various nutrition and health areas, distinguishing it from sibling tools that focus on other domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., herbapulse, mealpulse). Also lacks instructions on which endpoint to choose for a given task, requiring the agent to infer from endpoint names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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