emotion_get_analysis_prompt

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

Since no annotations are provided, the description carries the disclosure burden. It communicates that this is a retrieval step in a larger workflow (the tool returns data and the agent later submits changes), and that no external API Key is required. It does not explicitly state side effects or permissions, though the '获取' wording strongly implies a read-only operation.

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 front-loaded with the purpose and return contents, then adds workflow and rationale. Each sentence adds value, but the explanation of why to use the tool could be tightened, so it falls just short of 5.

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?

With no output schema, the description appropriately summarizes the return payload (current values, guide, message, history) and instructs the agent to produce JSON and call emotion_apply_deltas. It also addresses the environment (no API Key). It does not describe exact output shapes, but the returned guide presumably covers that, making it sufficiently complete for this 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?

Schema coverage is 100% with descriptions for all three parameters, so the description adds only modest value by mentioning '消息和对话历史' in the context of returned data rather than parameter semantics. It does not clarify user_id or provide formatting details beyond the schema, meriting the baseline 3.

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 identifies the tool as retrieving an emotion analysis task, with a specific verb '获取' and resource '情绪分析任务'. It lists the return contents (current values, guide, message/history) and the follow-up workflow, but it does not explicitly differentiate itself from the sibling tool emotion_get_emotion_prompt, so it misses the full 5.

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 when to use the tool by stating that after calling, the main LLM should analyze and then call emotion_apply_deltas; it also explains the no-API-key rationale. However, it does not explicitly compare alternatives or state when not to use it, so usage guidance is only implied.

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