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recommend_photo_pack

Identifies suitable photo packs for a user's goal or niche and uses industry or platform context to match visual needs.

Instructions

Recommend the best photo packs for a given user objective or niche.

Input Schema

NameRequiredDescriptionDefault
goalYesTarget goal (e.g. executive presence, travel lifestyle, dating).
industryNoTarget industry or platform.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
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 this is a read-only operation, how many recommendations are returned, whether results are ranked or explained, whether it requires an existing identity or photo pack set, or how it behaves when no packs match the goal.

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?

A single sentence with no wasted words, front-loaded with the verb and resource. It is efficient, though the brevity contributes to the missing usage and behavioral context.

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?

For a recommendation tool with no annotations, no output schema, and no sibling differentiation, the description is too thin. An agent cannot tell what a recommendation looks like, how it differs from search_photo_packs, or what prerequisites exist before calling it.

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 100%, so the schema already documents both parameters, and the baseline is 3. The description adds the framing that goal maps to a 'user objective or niche,' but it does not explain how industry/platform interacts with goal or what values are expected beyond the schema examples.

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?

States a specific verb and resource ('recommend the best photo packs') and a scope ('for a given user objective or niche'), so the core action is unambiguous. It does not distinguish itself from the sibling tools list_photo_packs and search_photo_packs, leaving the agent to infer whether this is retrieval or ranking.

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 phrase 'for a given user objective or niche' implicitly signals that this tool is for goal-driven selection rather than browsing or keyword search, which weakly differentiates it from search_photo_packs. However, there is no explicit when-to-use/when-not-to-use guidance or naming of the alternatives.

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