cluster_allocation_explain

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

No annotations are provided, so the description carries the full burden. It states the tool is for explanation/diagnosis, which implies it's a read-only operation, but doesn't explicitly confirm this or describe other behavioral traits like whether it requires specific permissions, what the output format is, or if it has side effects. For a diagnostic tool with zero annotation coverage, this leaves significant gaps in understanding how it 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 with a clear purpose statement, parameter explanations, and usage context in separate lines. It's appropriately sized with no redundant information, though it could be slightly more front-loaded by moving the usage context earlier. Every sentence adds value, making it efficient.

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 tool's complexity (diagnostic with 3 parameters) and no annotations or output schema, the description does a decent job: it explains the purpose, parameters, and usage context. However, it lacks details on behavioral traits (e.g., read-only nature, permissions) and output format, which are important for a diagnostic tool. It's minimally adequate but has clear gaps in completeness.

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 includes a parameter section that explains each parameter: 'index: 索引名称（可选，不传则解释第一个未分配分片）' (index name, optional, if not provided explains the first unallocated shard), 'shard: 分片编号' (shard number), 'primary: 是否主分片' (whether primary shard). With schema description coverage at 0%, this adds crucial meaning beyond the schema's basic types, clarifying optionality and default behavior. However, it doesn't cover all possible nuances like valid ranges for 'shard'.

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: '解释分片分配决策' (explain shard allocation decisions) and adds '用于诊断分片为什么未分配或分配到特定节点' (used to diagnose why shards are unallocated or allocated to specific nodes). This provides a specific verb ('explain/diagnose') and resource ('shard allocation decisions'), though it doesn't explicitly differentiate from sibling tools like 'cluster_reroute' or 'cat_shards' which are related to cluster/shard operations.

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 usage context: '用于诊断分片为什么未分配或分配到特定节点' (used to diagnose why shards are unallocated or allocated to specific nodes). This suggests when to use it (for diagnostic purposes), but doesn't explicitly state when not to use it or name alternatives among the many sibling tools (e.g., 'cluster_reroute' for changing allocations, 'cat_shards' for listing shards). The guidance is helpful but not comprehensive.

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