cluster_health

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the return values (cluster name, status, node count, shard count), it doesn't describe important behavioral aspects such as whether this is a read-only operation, potential performance impacts, error conditions, or authentication requirements. For a health-check tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 well-structured and appropriately concise. It uses three clear sections (purpose, parameters, returns) with minimal wasted text. Each sentence serves a distinct purpose: stating the tool's function, documenting parameters, and describing return values. The formatting with clear headings enhances readability.

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 that there are no annotations and no output schema, the description provides basic but incomplete context. It covers the purpose, parameters, and return values at a high level, which is adequate for a simple health-check tool. However, it lacks details about behavioral characteristics, error handling, and differentiation from sibling tools that would make it more complete for an AI agent.

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 description adds meaningful context for both parameters: 'index' is described as optional and for specifying an index, and 'level' is described as optional with possible values (cluster/indices/shards). Since schema description coverage is 0%, this compensates somewhat by providing basic semantics. However, it doesn't explain parameter interactions, default behaviors, or format requirements beyond what's minimally stated.

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: '获取集群健康状态' (Get cluster health status). It specifies the verb '获取' (get) and resource '集群健康状态' (cluster health status), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'cat_health' or 'cluster_stats', which appear to serve related but potentially different purposes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'cat_health', 'cluster_stats', or 'cluster_state', nor does it specify any prerequisites, contexts, or exclusions for usage. The agent must infer usage from the tool name and description alone.

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