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TrueLook: AI dating photos

Create photos

create_photos

Starts making photos of the user in the chosen styles (style ids from list_styles). Each style makes 4 photos and uses 4 credits. Confirm the styles with the user first. Photos take about 1 to 3 minutes; then call get_photos.

Input Schema

NameRequiredDescriptionDefault
stylesYesStyle ids, e.g. ["golf", "paris-cafe"].
connection_keyYesThe connection_key returned by connect_account in this conversation. Never show it to the user.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare the generic profile (readOnly=false, idempotent=false, openWorld=true). The description adds the material facts an agent cannot get from those hints: each style yields exactly 4 photos at a cost of 4 credits, and results take 1-3 minutes, which implicitly warns against duplicate submits on a non-idempotent, credit-consuming call.

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?

Three short sentences, front-loaded with the action, then cost/scale, then the confirmation rule and polling step. Every sentence carries operational information; nothing is restated from the schema or annotations.

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 two-parameter, no-output-schema action tool, the description supplies the full operating loop: pick styles, confirm with the user, invoke, wait 1-3 minutes, then fetch via get_photos. Cost and latency expectations are covered, so an agent needs nothing further to call it correctly.

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 coverage is 100%, so the baseline is 3, but the description earns a bump by tying the 'styles' parameter to its dependency (list_styles ids) and quantifying per-item cost and output (4 photos / 4 credits per style), which the schema's example alone does not convey. It does not address the maxItems=40 ceiling or what that implies for credit spend.

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?

States a specific verb and resource ('Starts making photos of the user') and scopes the input ('chosen styles'), immediately distinguishing it from get_photos (retrieval), list_styles (enumeration), and recommend_styles (suggestion). An agent can classify this tool without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit prerequisite ('Confirm the styles with the user first'), names the source of valid ids ('style ids from list_styles'), and specifies the follow-up route ('then call get_photos'). This covers when to use it and what to do next rather than leaving sequencing to inference.

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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