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Glama

hl_suggest_general_diet

Get general diet suggestions for wellness goals like anti-aging, energy, inflammation, gut health, or sleep. Provides non-personalized guidance without medical advice.

Instructions

Return general diet guidance for a wellness goal (anti_aging, energy_boost, anti_inflammatory, gut_health, sleep_improvement). No personal data. This is general wellness information, not medical advice. Consult a qualified healthcare professional for personal health decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNo
preferencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.2

TDQS

B3.2/5.0
Behavior3/5

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

The description discloses that no personal data is used and that it provides general wellness information, not medical advice. With no annotations provided, this is useful context, but it doesn't describe the output format or any other behavioral traits.

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?

The description is concise and front-loaded with the core purpose, followed by the disclaimer. It earns its place, though the goal list could be seen as schema-like detail.

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

Completeness3/5

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

For a simple two-parameter tool with no output schema, the description covers the main purpose and safety disclaimer. However, the 'preferences' parameter is completely undocumented, which is a notable gap for an agent trying to invoke the tool correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It lists the goal values (anti_aging, energy_boost, etc.) but does not explain the 'preferences' parameter at all, leaving the agent to guess its format and purpose.

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 tool returns general diet guidance for a wellness goal and lists the supported goals. It distinguishes itself from siblings by focusing on diet guidance, though it doesn't explicitly name a sibling alternative.

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

Usage Guidelines3/5

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

The description implies when to use it (when general diet guidance for a wellness goal is needed) and includes a disclaimer that it is not medical advice. However, it does not explicitly state when not to use it or mention alternatives like hl_suggest_general_motion for exercise guidance.

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