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DatingProfile: AI dating photos

List styles

list_styles
Read-onlyIdempotent

The 62 photo styles (scenes) DatingProfile can put the user in. Filter by category, photo type or a word. Set show_previews to see example photos of each style.

Input Schema

NameRequiredDescriptionDefault
searchNoA word to match, e.g. "beach", "dog" or "suit".
categoryNo
photo_typeNoOnly styles that fill this profile photo type.
show_previewsNoInclude example images (up to 8) of the matching styles.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without description help. The description contributes the useful fact that the catalogue is 62 styles total, but leaves out how filters combine and whether previews have a cost or latency impact. A minor tension exists: it says previews show 'example photos of each style' while the schema caps it at 'up to 8' matching styles.

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?

Three short sentences, front-loaded with the resource and its size, then filtering and then the preview option. Nothing is padded, though the parenthetical '(scenes)' is the only concession to redundancy and the opening noun phrase would read more decisively as a verb.

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

Completeness4/5

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

For a read-only, filter-only listing tool with no output schema and zero required parameters, this covers the essentials: what the items are, how many, how to narrow, and how to get images. The remaining gap is not stating what each returned style contains (name, id, category) that a downstream create_photos call would need, plus the filter-combination rule.

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 coverage is 75%, so the schema already carries most parameter meaning, and the baseline of 3 applies. The description confirms the three filtering dimensions but adds no semantics the schema lacks — notably it never says whether search, category and photo_type are AND-ed together, which is the one clarification that would materially help.

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 names the concrete resource (62 photo styles/scenes) and the operations available on it (filter by category, photo type, or word; optionally include previews), so an agent knows exactly what it returns. It stops short of a leading verb and never explicitly contrasts itself with the sibling recommend_styles, which is the main ambiguity for selection.

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?

Usage is implied rather than stated: 'Filter by category, photo type or a word' tells how to narrow results and 'Set show_previews to see example photos' tells how to enrich them. There is no explicit when-to-use guidance and no exclusion pointing to recommend_styles as the alternative when the user wants a suggestion rather than a browsing list.

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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