cls_describe_topics

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 effectively describes the tool's behavior as a read-only query operation (implied by '查询'), includes pagination details (offset/limit defaults), filtering options, and region handling. It also outlines the return information structure, though it doesn't cover aspects like error conditions, rate limits, or authentication needs, which keeps it from a perfect score.

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 clear sections (purpose, parameter explanations, return info) and uses bullet points for readability. It is appropriately sized, though the parameter section is lengthy due to covering all parameters—this is necessary given the lack of schema descriptions, so it earns its place without being wasteful.

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?

For a query tool with 6 parameters, 0% schema coverage, no annotations, but an output schema, the description is quite complete. It explains the tool's purpose, all parameters in detail, and the return information. The output schema likely covers return values, so the description doesn't need to duplicate that. Minor gaps include lack of error handling or explicit sibling tool comparisons, but overall it provides sufficient context for effective use.

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?

Given 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all 6 parameters. It clarifies defaults (e.g., offset=0, limit=20), optionality, filtering logic (e.g., fuzzy matching for topic_name), enum values for biz_type (0 for log topics, 1 for metric topics), and region usage with a reference to another tool. This adds significant value 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 as '查询日志主题列表' (query log topic list) and explains that log topics are basic storage units for log data. This provides a specific verb ('query') and resource ('log topic list'), though it doesn't explicitly differentiate from sibling tools like 'cls_describe_logsets' or 'cls_describe_topic_detail' beyond the resource type.

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 guidance through parameter explanations (e.g., '当需要查询指标主题时，请传入 biz_type=1' for querying metric topics, and mentioning 'cls_describe_regions' for available regions). However, it lacks explicit when-to-use vs. alternatives (e.g., compared to 'cls_describe_topic_detail' for detailed info) or prerequisites, leaving room for improvement.

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