photo_randomRetrieve one or more random Unsplash photos; supports optional filters (query, orientation, collections, topics, username, content_filter) passed as extra params.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Unique photo identifier | |
| urls | No | Photo URLs at different sizes | |
| user | No | Photo author information |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and openWorld hints, so the description only adds minor context: the ability to return multiple photos and apply filters. It does not detail pagination, rate limits, or response structure, but the output schema covers return values. This is adequate but not overly rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the primary action ('Retrieve one or more random Unsplash photos') and efficiently groups the filter options. No redundant or filler words are present, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of annotations (readOnly, idempotent, openWorld) and an output schema, the description is fairly complete for this simple tool. It covers the core behavior and filter options, but does not mention count or how extras are passed in practice; this leaves minor ambiguity for an agent. Overall, it is contextually adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema defines zero properties, so the description's mention of 'extra params' (query, orientation, collections, topics, username, content_filter) adds essential semantic value beyond the empty schema. However, it omits the 'count' parameter shown in examples, and does not specify parameter types or formats. Still, the listed filters provide a solid baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves random Unsplash photos, distinguishing it from sibling search/list tools. The verb 'Retrieve' and specific resource 'random Unsplash photos' make the purpose unambiguous. Mentioning optional filters further clarifies scope without confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use this for random photo retrieval, and lists the available filter parameters. It does not explicitly name alternatives like search_photos or list_photos, but the random nature implies when to use this tool. No exclusionary guidance is needed since the use case is evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.