Alibaba Cloud Observability MCP Server

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 effectively discloses behavioral traits: it describes the return data structure in detail ('返回数据结构' section), including keys like alias, sensitive, type, and json_keys. It also specifies that parameters '必须精确匹配' (must exact match) and provides query examples. However, it doesn't mention potential errors, rate limits, or authentication needs, which are gaps for a tool with no annotations.

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 structured with sections (功能概述, 使用场景, 返回数据结构, 查询示例, Args, Returns), which aids readability. However, it includes redundant elements: the Args and Returns sections largely repeat information from the schema and return structure description, and the query examples are somewhat verbose. While not overly long, it could be more front-loaded and efficient, with some sentences not earning their place fully.

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 (3 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, usage scenarios, return data structure, and parameter basics. The lack of output schema is mitigated by the detailed return structure explanation. However, it misses some contextual details like error handling or dependencies, which would enhance completeness for a tool with no annotations.

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?

Schema description coverage is 100%, so the schema already documents all three parameters with descriptions (e.g., 'must exact match, not fuzzy search'). The description adds minimal value beyond the schema: it repeats the exact match requirement in Chinese and lists parameters in the Args section without additional semantics. This meets the baseline of 3, as the schema does the heavy lifting, but the description doesn't compensate with extra insights like format examples or constraints.

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SLS日志库的结构信息' (Get SLS log store structure information) and elaborates with '获取指定SLS项目中日志库的索引信息和结构定义' (Get index information and structure definition of a specified SLS project's log store). It specifies the verb '获取' (get) and resource 'SLS日志库的结构信息' (SLS log store structure information). However, it doesn't explicitly differentiate from sibling tools like 'sls_list_logstores' or 'sls_execute_query', which reduces clarity slightly.

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 clear usage scenarios in a '使用场景' (Usage scenarios) section, listing four specific cases (e.g., '当需要了解日志库的字段结构时' - When needing to understand the field structure of a log store). It implicitly distinguishes from siblings by focusing on structure retrieval rather than listing or querying. However, it lacks explicit when-not-to-use guidance or named alternatives, such as contrasting with 'sls_execute_query' for actual data queries.

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