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Wardrobe Capsule

Wardrobe Capsule

packing_list

Builds a multi-day packing list from your wardrobe using trip length, weather, and occasions, flagging missing items.

Instructions

A trip packing list from your real items.

days is trip length (>=1), temp_c the average temperature (or weather_words like 'cool and rainy'), occasions a comma list per day (default casual, e.g. 'casual, work, fancy').

Input Schema

NameRequiredDescriptionDefault
daysYes
temp_cNo
occasionsNo
weather_wordsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does not state whether the tool only reads wardrobe data, whether it writes or stores the generated list, what permissions are required, or whether the packing list can be regenerated safely.

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 short and front-loads the purpose before explaining parameters. The parameter sentence is dense but efficient; the only minor weakness is slightly awkward grammar and line breaks.

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?

Because an output schema exists, the description need not explain return values. However, with no annotations and several sibling tools, it is missing enough routing guidance and behavioral context to be fully complete for an agent deciding when and how to call it.

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

Parameters4/5

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, and it does so well: days is defined as trip length with a >=1 constraint, temp_c as average temperature, weather_words with an example, and occasions as a comma-separated per-day list with a default. It adds substantial meaning beyond the bare schema.

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

Purpose3/5

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

The description identifies the artifact as a trip packing list built from the user's real items, which is more specific than the tool name alone. However, it does not use a clear verb such as generate/create and does not explicitly distinguish the tool from the sibling suggest_outfit, leaving the agent to infer the exact operation.

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?

The description implies a trip-planning context but gives no explicit guidance on when to use this tool versus suggest_outfit or other wardrobe siblings. It also provides no conditions, prerequisites, or exclusions to route the agent correctly.

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