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by ai.switchapp

Apply Wellness

apply_wellness
Read-onlyIdempotent

Wellness / yoga / fitness / lifestyle campaign — warm amber tropical, tropical paradise cinematic, or high-key cyan beach. Returns the styled prompt stack for your shot — pair it with generate_image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleYeswarm_amber_tropical = warm honey grade with golden haze. hanalei_cinematic = soft golden mist + infinity pool reflection. high_key_cyan_beach = bright daylit cyan ocean.
subjectNoWhat you want to shoot. E.g. "a woman walking through a hotel lobby" or "morning coffee on the balcony".

TDQS

A4.1/5.0
Behavior4/5

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

With readOnly and idempotent annotations already present, the description adds that the tool returns a prompt stack rather than an image, and that it should be paired with generate_image. This contextualizes the output without contradicting annotations.

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?

Two concise sentences, front-loaded with the domain and styles, no filler. Every sentence earns its place.

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

Completeness5/5

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

For a simple style tool with 2 parameters and full schema coverage, the description sufficiently explains the output (prompt stack) and next step (use generate_image). No output schema is required and nothing critical is missing.

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?

The schema provides 100% coverage, including detailed enum descriptions for style and an example for subject. The description does not need to add parameter details, so baseline 3 is appropriate.

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 identifies the tool as applying wellness/yoga/fitness/lifestyle campaign styles (warm amber, cinematic, or cyan beach) and states it returns a styled prompt stack to pair with generate_image. This distinguishes it from sibling style tools by domain and output type.

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 usage for wellness-themed shots and instructs pairing with generate_image, but does not explicitly state when to choose this over sibling apply_* tools (e.g., apply_travel) or any exclusions. It provides a clear context but no direct alternatives.

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

A3.5/5.0
Disambiguation2/5

Several tools occupy nearly identical semantic ground: apply_iphone_realism and apply_ugc both describe casual phone-shot looks, upload_media and upload_reference_asset both accept uploads, and analyze_video overlaps heavily with analyze_video_report. The many apply_* style tools are essentially one tool parameterized by style, so agents can easily select the wrong one.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern such as generate_image, list_my_videos, get_editor_run, and upscale_video. A few outliers like voice, talking_avatar_video, and video_to_prompt do not use the same verb-first convention, but they are still readable and do not create significant confusion.

Tool Count1/5

At 55 tools, the surface is far beyond what is appropriate for an MCP server; many of these be collapsed or parameterized, especially the 10 apply_* style wrappers and several overlapping upload/status helpers. Even for a broad media platform, this scale forces a huge context window and makes selecting the right tool impractical.

Completeness2/5

The surface covers generation, media display, video analysis, and Editor workflows well, but there are obvious gaps in library lifecycle management: move_asset and create_folder are referenced in tool descriptions without being exposed, and there is no clean way to delete or reorganize media assets. Agents following the descriptions will try to call tools that do not exist.

Resources