Atlas Cloud MCP Server (Image / Video / LLM APIs)

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world hints, covering safety and behavior. The description adds useful context by specifying the return format (Markdown-formatted list) and content (models with descriptions, pricing, links), which goes beyond annotations. No contradiction with annotations.

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 well-structured and front-loaded with the core purpose, followed by usage guidelines, parameter info, return format, and examples. Every sentence adds value without waste, making it efficient and easy to parse.

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 tool's low complexity (1 parameter, 100% schema coverage), rich annotations, and no output schema, the description is complete. It covers purpose, usage, return format, and examples, providing sufficient context for an agent to use the tool effectively without over-explaining.

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?

Schema description coverage is 100%, with the schema fully documenting the single 'query' parameter. The description adds minimal extra meaning by listing examples of what the query can match (e.g., model names, types, providers, tags), but this is largely redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 searches Atlas Cloud documentation, models, and API references by keyword, specifying it returns matching models with descriptions, pricing, and links. It distinguishes from sibling atlas_get_model_info by noting that tool is for detailed API docs of a specific model, making the purpose specific and differentiated.

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 explicitly provides when to use this tool (search by keyword across models, types, providers, tags) and when not to use it (for detailed API docs of a specific model, use atlas_get_model_info instead), offering clear alternatives and context.

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