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get_mars_rover_photos

Retrieve Mars rover photos from Curiosity, Opportunity, or Spirit by specifying either Martian sol or Earth date and optional camera filters.

Instructions

Get photos from a Mars rover (Curiosity, Opportunity, Spirit). Specify either sol (Martian day) or earth_date (YYYY-MM-DD), but not both.

Args: rover_name: Name of the rover (curiosity, opportunity, spirit). sol: Martian sol (day number, starting from landing). Use if not using earth_date. earth_date: Earth date in YYYY-MM-DD format. Use if not using sol. camera: Filter by camera abbreviation (e.g., FHAZ, RHAZ, MAST, NAVCAM, PANCAM). See documentation for full list per rover. page: Page number for results (25 photos per page).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rover_nameYes
solNo
earth_dateNo
cameraNo
pageNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses basic behavioral traits like the exclusive choice between sol and earth_date, and pagination (25 photos per page), but lacks details on rate limits, error handling, or authentication needs. This is adequate but has gaps for a tool with no annotation support.

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?

The description is front-loaded with the core purpose, followed by a structured list of parameters with clear explanations. Every sentence adds value without redundancy, making it efficient and easy for an AI agent to parse.

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?

Given the complexity (5 parameters, no annotations, no output schema), the description is largely complete, covering purpose, usage rules, and parameter details. However, it lacks information on return values or error cases, which would enhance completeness for a tool with no output schema.

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?

With 0% schema description coverage, the description compensates well by explaining each parameter's purpose and constraints (e.g., sol vs. earth_date exclusivity, camera abbreviations, page usage). It adds meaningful semantics beyond the bare schema, though it could provide more on default behaviors or validation rules.

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 states the tool's purpose with a specific verb ('Get photos') and resource ('from a Mars rover'), and it distinguishes the tool from siblings by specifying the rovers (Curiosity, Opportunity, Spirit). This is precise and actionable for an AI agent.

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?

The description provides explicit usage guidance by stating 'Specify either sol (Martian day) or earth_date (YYYY-MM-DD), but not both,' which helps the agent avoid conflicts. It also lists camera options and pagination details, offering clear context for when to use parameters.

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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