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check_full_stack

Check a complete supplement and medication stack for all interactions, conflicts, synergies, and generate a full daily timing schedule. Use this when a user wants to check their entire supplement regimen or build a complete daily schedule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bedtimeNoBedtime HH:MM
wake_timeNoWake time in HH:MM format. e.g. '07:00'
dinner_timeNoDinner time HH:MM
medicationsNoAll prescription medications.
supplementsYesAll supplements and vitamins.
breakfast_timeNoBreakfast time HH:MM

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the core behavior (checking interactions and generating a schedule) but omits details about the output format, handling of missing times, or how conflicts are reported. It is accurate but shallow.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core function and a clear usage case. There is no filler; every clause adds value.

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?

Despite having six parameters and producing a complex schedule, the description does not explain the schedule output, the optionality of time parameters, or how missing times are handled. With no output schema, this is a significant gap for an agent to correctly invoke and interpret the result.

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%, meaning every parameter already has an explanation in the schema. The description adds no additional parameter semantics, so the baseline of 3 applies. It does not clarify relationships between time parameters or how they influence the schedule.

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 states a specific verb ('check') and resource ('complete supplement and medication stack'), and clearly outputs a 'full daily timing schedule.' It also explicitly contrasts with checking individual items, which distinguishes it from siblings like check_supplement_safety and get_supplement_timing.

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?

It provides a clear when-to-use directive ('when a user wants to check their entire supplement regimen or build a complete daily schedule'), but does not explicitly state when NOT to use it or name alternative tools. The sibling names are present in the context, but the description itself does not contrast with them explicitly.

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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TDQS

A3.9/5.0
Disambiguation2/5

check_supplement_safety overlaps heavily with get_supplement_timing, grade_supplement_quality, and verify_nih_label by returning timing, quality grade, filler detection, and NIH verification alongside safety data. This creates unclear boundaries and makes tool selection ambiguous.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: check_full_stack, check_supplement_safety, get_supplement_timing, grade_supplement_quality, verify_nih_label. The naming is predictable and easy to navigate.

Tool Count5/5

Five tools is a well-scoped size for the supplement advisory domain. Each tool covers a distinct high-level concern, and the count is neither bloated nor too thin.

Completeness4/5

The tool set covers full-stack interaction checking, individual safety checks, timing, quality grading, and NIH label verification. Minor gaps exist around detailed supplement information retrieval, but the core domain is functionally complete.