ask_deepseek

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

No annotations are provided, so the description carries the full burden. It mentions the tool can 'ask a question' or 'get a general second opinion,' but lacks details on behavioral traits such as response format, rate limits, authentication needs, or whether it's read-only or mutative. This is a significant gap for an AI query tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core purpose. It uses clear language with zero waste, making it easy to understand quickly without unnecessary elaboration.

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 (querying an AI model) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the response looks like, potential limitations, or how it integrates with other tools like context_get. For a tool with no structured behavioral data, more context is needed.

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%, so the schema already documents both parameters (context_id and question). The description adds minimal value beyond the schema by implying that 'question' is optional and if omitted, it defaults to a 'general second opinion.' This aligns with the schema but doesn't provide additional syntax or format details.

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's purpose: 'Ask DeepSeek a question about a context entry, or get a general second opinion.' It specifies the verb ('ask') and resource ('DeepSeek'), though it doesn't explicitly differentiate from sibling tools like ask_chatgpt, ask_claude, or ask_gemini beyond naming the specific AI model.

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 by mentioning 'about a context entry' and 'general second opinion,' suggesting it's for querying AI models. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like ask_chatgpt or context_search, nor does it specify prerequisites or exclusions.

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