atom-mcp-server

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by specifying return fields (vendor name, country, region, pricing page URL) and categorization schema (four channel types), compensating for missing output schema. However, it omits rate limits, pagination behavior, or detailed auth implications beyond the schema.

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?

Front-loaded with purpose ('List all AI inference vendors'), followed by return value, categorization context, then examples. Every sentence earns its place. The structure progresses logically from what it does to what it returns to how to use it, with no redundant text.

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?

Adequately compensates for missing output schema by listing return fields. Covers all 3 parameters (0 required) and their optional nature. Minor gap: doesn't mention pagination, result limits, or whether the vendor list is exhaustive vs. curated, which would be useful for a 'list all' tool.

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 coverage is 100%, so baseline is met. The description adds semantic context via examples showing how 'European' maps to region and 'Chinese' maps to country, clarifying the filter intent. However, it doesn't add syntax details, validation rules, or explain the _atom_api_key behavior beyond the schema description.

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?

Specific verb 'List' + resource 'AI inference vendors' + scope 'tracked by ATOM'. Distinguishes from siblings by specifying it returns basic metadata (name, country, region, pricing URL) and spans four channel types, differentiating it from get_vendor_catalog or compare_prices.

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?

Provides three concrete examples mapping natural language queries to parameter usage ('European AI vendors' → region='Europe'), effectively demonstrating when to apply filters. Lacks explicit 'when not to use' or alternative naming (e.g., doesn't say 'use compare_prices for price comparisons'), but the examples provide clear contextual guidance.

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