get_system_health

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 mentions the type of information returned (performance metrics, resource usage, recommendations) but does not disclose whether this is a read-only operation, how the data is structured, whether any side effects occur, or any rate limits/auth requirements. The absence of these details leaves significant behavioral uncertainty for a health-check tool.

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, concise sentence that front-loads the primary action and content scope. It avoids unnecessary words and is appropriately sized for a simple health-check tool. However, the term '建议' (recommendations) is slightly ambiguous and could be more specific.

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 no annotations, no output schema, and only a one-sentence description, the tool is underspecified. It does not explain what constitutes 'system health', how the returned recommendations are formatted, or how this tool relates to sibling tools like get_performance_stats and optimize_performance. The agent would need to guess at output structure and use context.

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 has 100% description coverage for the single optional parameter 'include_recommendations' (default true), which is fully documented as controlling whether optimization suggestions are included. Per the baseline rule, a score of 3 is appropriate because the schema handles the parameter semantics and the description adds no additional context.

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 a specific action ('获取系统健康状态' / get system health) and lists its content areas (performance metrics, resource usage, recommendations). It is unambiguous and distinct from most siblings, though it does not explicitly differentiate from the similar-looking get_performance_stats.

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 guidance is provided on when to use this tool versus alternatives such as get_performance_stats or get_cache_stats. There is no mention of typical scenarios, prerequisites, or exclusion criteria, leaving the agent to infer usage from the tool's name and generic description.

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