Deepghs MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond this by specifying that these are 'public Spaces (live demo apps)' and listing concrete examples of what they include. It also mentions the return format details (SDK type, likes, update dates, direct links), which isn't covered by 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 with a clear purpose statement, examples, and parameter/return sections. It's appropriately sized for the tool's complexity. The only minor improvement would be to integrate the examples more seamlessly rather than as a separate bulleted list.

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 moderate complexity, rich annotations, and the presence of an output schema, the description is complete. It covers purpose, examples, parameters, and return format. The output schema handles return value details, so the description doesn't need to duplicate that information.

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 0%, so the description carries full burden. It provides clear explanations for all three parameters (search, limit, response_format) with examples and constraints. The only minor gap is that it doesn't explicitly mention the default values that are documented in the schema.

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 specific action ('List all public Spaces') and resource ('from the DeepGHS organization on HuggingFace'), with examples of what these spaces include. It distinguishes this tool from siblings like 'deepghs_list_datasets' and 'deepghs_list_models' by focusing specifically on Spaces/live demo apps rather than datasets or models.

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 Spaces are included (reverse image search, Danbooru character lookup, etc.), which helps the agent understand when this tool is appropriate. However, it doesn't explicitly state when to use alternatives like 'deepghs_list_datasets' or 'deepghs_list_models', nor does it provide exclusion criteria.

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