emotion_get_emotion_prompt

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

No annotations are provided, so the description carries the burden. It clearly indicates a read/generate operation ('generate', 'based on current emotion values'), implying no mutation. However, it does not disclose potential side effects, required permissions, or output format details, which is a notable gap but acceptable for a simple getter.

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 action and includes the key purpose. Every word adds value with no redundancy.

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 low complexity (one parameter, no output schema), the description adequately explains what the tool returns (emotion value text for system prompt) and its use case. It could specify format details or edge cases, but it is complete enough for an agent to understand and invoke the 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?

The input schema already fully documents the only parameter, user_id, as '用户唯一标识' (user unique identifier). The description adds no additional parameter context, so it neither enhances nor detracts from schema coverage. Baseline of 3 is appropriate.

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?

Description states a specific action: 'Generate emotion value text that can be injected into system prompt, enabling the AI to role-play based on current emotion values.' It clearly identifies the resource (emotion values) and the output (injectable prompt text), and the explicit mention of 'system prompt' distinguishes it from sibling tools like emotion_get_status and emotion_get_analysis_prompt.

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 gives clear context for when to use: when a system prompt with current emotion values is needed for role-play. It implicitly differentiates from sibling tools by focusing on prompt generation, but it does not explicitly name alternatives or state 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.