cls_describe_dashboards

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 mentions pagination (offset/limit) and optional filtering, but doesn't disclose critical behavioral traits: whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what happens if no dashboards exist. For a list tool with zero annotation coverage, this leaves significant gaps.

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 sized. It starts with a clear purpose statement, followed by a parameter section with bullet points. Every sentence earns its place, though it could be slightly more front-loaded by integrating parameter hints into the initial summary. No wasted text.

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 moderate complexity (list operation with filtering/pagination), no annotations, but with an output schema (which handles return values), the description is fairly complete. It covers all parameters thoroughly and references related tools. However, it lacks behavioral context (e.g., safety, limits), which is a minor gap since the output schema exists.

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 0%, so the description must compensate fully. It does so excellently: it explains all 4 parameters with clear semantics—offset as pagination offset, limit as items per page, dashboard_name for filtering, and region with examples and a reference to another tool for valid values. This adds substantial meaning beyond the bare schema.

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: '查询仪表盘列表。获取当前账号下的 CLS 仪表盘。' (Query dashboard list. Get CLS dashboards under the current account.) This specifies the verb ('query/list') and resource ('CLS dashboards'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'cls_describe_regions' or 'cls_describe_topics', which describe other resources.

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 some implied usage context: it mentions filtering by dashboard name and region, and references 'cls_describe_regions' for available regions. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., no comparison to other 'describe' tools for dashboards or search functions). The context is clear but not comprehensive.

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