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 safety and idempotency. The description adds valuable context beyond annotations by specifying the source (HuggingFace), the organization (DeepGHS), and the return format details (paginated list with task type, download counts, likes, and links), enhancing behavioral understanding without contradictions.

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 appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured clearly, though the list of model types adds some bulk; overall, it remains efficient with minimal waste.

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 an output schema (implied by Returns section), the description is complete. It covers purpose, parameters, return values, and context, leaving no significant gaps for agent understanding.

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 effectively adds meaning by explaining each parameter in the Args section with examples and defaults (e.g., search keyword filters, sort options, limit range, pagination offset, response format choices), compensating well for the lack of schema descriptions.

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 models from the DeepGHS organization on HuggingFace,' making the purpose specific. It distinguishes from siblings by focusing on models rather than datasets, spaces, tags, or other resources, and provides examples of included model types like CCIP and WD Tagger Enhanced.

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 implies usage for listing models with filtering and pagination, but does not explicitly state when to use this tool versus alternatives like deepghs_list_datasets or deepghs_list_spaces. It provides context by listing model types, which helps identify relevant use cases, but lacks explicit exclusions or named alternatives.

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