case_study

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'analyze' without explaining what the analysis entails, whether it's read-only or modifies data, what permissions are needed, or how results are returned. This is inadequate for a tool with 4 parameters and no output schema, leaving key behavioral traits unspecified.

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 phrase in Chinese, front-loaded with the core action. There is no wasted verbiage or redundancy, making it highly concise. However, this conciseness comes at the cost of detail, which is reflected in lower scores for other dimensions.

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 complexity (4 parameters, no annotations, no output schema) and sibling tools, the description is incomplete. It doesn't explain the tool's behavior, output format, or differentiation from alternatives. The schema covers parameters well, but the description fails to provide necessary context for effective use, especially without annotations or output schema.

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 schema description coverage is 100%, with clear descriptions for all parameters (e.g., 'case_id' specifies optional retrieval, 'system' defines case types). The description adds no additional meaning beyond the schema, such as explaining how 'analysis_focus' interacts with 'system' or providing examples. Baseline 3 is appropriate since the schema does the heavy lifting.

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 '分析易经和八字案例' (analyze Yijing and Bazi case studies) states a general purpose but is vague about what 'analyze' entails. It doesn't specify if this tool retrieves, processes, or interprets case studies, nor does it distinguish itself from sibling tools like 'bazi_analyze', 'combined_analysis', or 'yijing_interpret'. The description restates the tool name's concept without adding specificity.

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?

No explicit guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions. Given sibling tools like 'bazi_analyze' and 'yijing_interpret', the lack of differentiation leaves the agent uncertain about when this tool is appropriate, relying solely on the input schema for hints.

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