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EricGrill

Civic Data MCP Server

by EricGrill

query_nasa

Query NASA's public APIs to retrieve space data, imagery, and scientific information by specifying endpoints and parameters.

Instructions

Make a raw query to the NASA API.

Args:
    endpoint: API endpoint (e.g., '/planetary/apod', '/neo/rest/v1/feed')
    params: Query parameters (api_key will be added automatically)

Returns:
    Raw JSON response from NASA API

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endpointYes
paramsNo
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 burden. It mentions that 'api_key will be added automatically,' which is useful context about authentication. However, it lacks details on rate limits, error handling, or response behavior beyond 'Raw JSON response,' leaving significant gaps for a tool that interacts with an external API.

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?

The description is appropriately sized and front-loaded, starting with the core purpose. The structured 'Args' and 'Returns' sections are efficient, though the example for 'endpoint' could be more concise. Overall, it avoids unnecessary verbosity.

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?

Given the complexity of querying an external API with no annotations and no output schema, the description is incomplete. It lacks details on authentication, rate limits, error cases, and the structure of the 'Raw JSON response,' making it inadequate for safe and effective use by an agent.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining 'endpoint' with examples (e.g., '/planetary/apod') and 'params' as query parameters with the note about api_key. This provides basic semantics beyond the bare schema, but it doesn't fully document all aspects like parameter formats or constraints.

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 clearly states the tool's purpose: 'Make a raw query to the NASA API.' It specifies the verb ('query') and resource ('NASA API'), though it doesn't explicitly differentiate from sibling tools like 'search_nasa_images' or 'get_astronomy_photo' beyond being a 'raw query' versus more specialized functions.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_nasa_images' or 'get_astronomy_photo', nor does it specify use cases or exclusions, leaving the agent to infer usage from the generic 'raw query' phrasing.

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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