sls_list_logstores

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 key behaviors: the tool lists log stores with fuzzy search capabilities, defaults to log store type if unspecified, supports pagination via limit (range 1-100), and distinguishes between log and metric stores. It doesn't mention rate limits, authentication needs, or error handling, but covers core operational traits well.

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 (功能概述, 使用场景, etc.), but it includes redundant information. The Args and Returns sections repeat what's in the schema, and the query examples add little practical value. While not overly verbose, some content doesn't earn its place, reducing efficiency.

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 tool with 6 parameters, no annotations, and no output schema, the description does a good job. It explains the tool's purpose, usage, and key behaviors, and the schema covers parameter details. The main gap is the lack of output format explanation beyond '日志库名称的字符串列表' (list of log store names), but given the tool's simplicity, this is sufficient.

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 parameters thoroughly. The description adds minimal value beyond the schema: it mentions fuzzy search for log_store and clarifies is_metric_store usage in a dedicated section. However, it doesn't provide additional context like examples for region_id format or interactions between parameters. Baseline 3 is appropriate given the schema does most of the work.

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: '列出SLS项目中的日志库' (list log stores in SLS projects). It specifies the exact action (list) and resource (log stores), and distinguishes it from siblings like sls_describe_logstore (which describes a single log store) and sls_list_projects (which lists projects). The functional overview reinforces this with details about fuzzy search and default behavior.

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 explicit usage scenarios: finding if a specific log store exists, getting all available log stores, or searching by partial name. It also includes a dedicated section '是否指标库' (Is it a metric store) that explicitly guides when to set is_metric_store to True versus False, offering clear alternatives for different data types.

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