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check_stack

Audit a supplement or ingredient stack in one call: get per-item condition-lens verdicts with evidence grading, plus curated ingredient-to-ingredient interactions found within the stack.

Instructions

Audit a supplement/ingredient STACK in one call: per-item condition-lens verdicts (evidence-graded, cited where citations exist) PLUS every curated ingredient-to-ingredient interaction found WITHIN the stack (type, severity, mechanism, source). Use when a user takes multiple supplements together. Supports multi-lens via lenses. Absence of an interaction is NOT proof of safety — the curated set is growing. Every result includes human_url for the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensNoSingle condition lensall
lensesNoMultiple condition lenses in one call (max 5); wins over `lens` when provided
ingredientsYes2-12 ingredient/supplement names, e.g. ['iron','calcium','quercetin']
Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses key behaviors: that the curated set is growing, that results include evidence-graded verdicts and interactions with type, severity, mechanism, and source. Also mentions human_url. No contradictions.

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

Conciseness4/5

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

Two sentences, front-loaded with purpose. Some redundancy ('supplement/ingredient STACK' vs 'multiple supplements') but overall efficient. Every sentence adds value.

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

Completeness4/5

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

No output schema, but description explains what results include (verdicts, interactions, type, severity, etc.). It also includes a safety caveat. For a complex tool with multiple inputs and outputs, the description is adequately complete.

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 coverage is 100%, so baseline is 3. The description explains the tool's output (per-item verdicts, interactions) but adds little meaning to individual parameters beyond what the schema already provides. It implies the function of 'lens' and 'lenses' but doesn't elaborate on format or constraints.

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

Purpose5/5

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

The description uses specific verbs ('audit', 'plus') and clearly identifies the resource ('supplement/ingredient STACK'). It distinguishes from sibling tools like check_ingredient (single) and check_interaction (pairwise) by focusing on multi-ingredient stacks.

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

Usage Guidelines4/5

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

Explicitly states when to use ('when a user takes multiple supplements together'). Also warns that absence of an interaction is not proof of safety, providing critical context. Does not list alternatives or when not to use, but the purpose is clear.

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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