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generate_packing_list

Create a tailored packing list for any trip by factoring in destination, climate, and planned activities.

Instructions

Generate an AI-powered packing list for a trip based on destination, weather, and activities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whenNoWhen the trip occurs (month, season, or dates)
destinationYesTravel destination
itinerary_idNoGenerate from existing itinerary ID
trip_detailsNoTrip activities or purpose

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.2

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It only states that the tool generates an AI-powered list, but does not disclose whether this is a read-only operation, whether it modifies any data, what the output format is, or whether it depends on external services. The lack of detail leaves important behavior undisclosed.

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 a single, focused sentence that front-loads the action and purpose. There is no wasted wording; it conveys the core function efficiently.

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?

Given the absence of annotations and output schema, the description should explain what the tool returns (e.g., a list format), any prerequisites, and potential side effects. It does none of this, leaving the tool's behavior and expected results under-specified for an agent to invoke it confidently.

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 mentions 'destination, weather, and activities' which loosely maps to destination and trip_details parameters, but it does not add any semantic detail beyond what the schema already provides, such as how 'when' affects weather or the relationship between parameters.

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 clearly states the verb 'Generate' and the resource 'packing list', along with the basis (destination, weather, activities). It is unambiguous and distinct from all sibling tools, none of which focus on packing lists.

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 the use case (trip planning based on destination and activities) but does not explicitly state when to choose this tool over alternatives or mention any exclusions. Sibling tools like ask_travel_expert or get_weather_insights are not referenced, so the agent must infer the appropriate context.

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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curl -X GET 'https://glama.ai/api/mcp/v1/servers/klabianco/plantrip-mcp-server'

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