Deepghs MCP

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering the safety profile. The description adds useful context about pagination behavior and response formats, but doesn't disclose rate limits, authentication requirements, or other operational constraints beyond what annotations provide.

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 with a clear purpose statement, context about available datasets, and organized parameter documentation. It's appropriately sized for a tool with multiple parameters, though the dataset examples list could be slightly more concise. Every sentence adds value to understanding the tool.

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 complexity (5 parameters with 0% schema coverage) and the presence of output schema, the description provides complete context. It explains what the tool does, what parameters control, and what to expect in the return value. The output schema handles return value details, so the description appropriately focuses on usage context.

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?

With 0% schema description coverage, the description carries the full burden of parameter documentation. It provides clear explanations for all 5 parameters (search, sort, limit, offset, response_format) with examples and constraints, effectively compensating for the schema's lack of descriptions. The only minor gap is not explicitly stating that 'params' is a wrapper object.

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 verb ('List') and resource ('all public datasets from the DeepGHS organization on HuggingFace'), providing specific examples of datasets included. It distinguishes this tool from siblings like deepghs_list_models and deepghs_list_spaces by focusing specifically on datasets rather than other HuggingFace resources.

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 provides clear context about what types of datasets are available (Danbooru2024, Sankaku, etc.), helping users understand when this tool is appropriate. However, it doesn't explicitly state when to use alternatives like deepghs_find_character_dataset or deepghs_search_tags, nor does it provide exclusion criteria for when not to use this tool.

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