Alibaba Cloud Observability MCP Server

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

With no annotations provided, the description carries full burden. It discloses that queries must use SLS syntax (not natural language), specifies required time range parameters, mentions error handling scenarios, and indicates results are returned as a list of log records. However, it doesn't cover important behavioral aspects like authentication requirements, rate limits, pagination behavior, or what happens with malformed queries beyond the specific error example.

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 excessively long with redundant sections. The 'Args' and 'Returns' sections duplicate information that should be in the schema. The query examples are in natural language despite explicitly stating queries must use SLS syntax, creating confusion. The error handling section is overly specific to one sibling tool interaction. Much of this content could be streamlined or moved to structured documentation.

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 7-parameter query execution tool with no annotations and no output schema, the description provides adequate functional coverage but lacks important operational context. It explains what the tool does and when to use it, but doesn't sufficiently cover error patterns beyond one example, performance characteristics, or result format details. The description compensates somewhat for the lack of structured metadata but leaves gaps in behavioral transparency.

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 7 parameters thoroughly. The description adds minimal value beyond the schema - it mentions time range requirements and provides an example limit value, but doesn't explain parameter interactions, constraints beyond what's in the schema, or the significance of region_id selection. The baseline 3 is appropriate when the schema does the heavy lifting.

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 'executes SLS log queries' with specific resources (SLS project and log store) and mentions returning query results. It distinguishes from siblings like sls_describe_logstore and sls_translate_natural_language_to_query by focusing on query execution rather than metadata or translation. However, it doesn't explicitly contrast with sls_diagnose_query which might have overlapping functionality.

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 '使用场景' section provides clear context for when to use this tool (querying logs with specific conditions, time ranges, events, or aggregations). It explicitly references sibling tools sls_describe_logstore and sls_translate_natural_language_to_query for prerequisite steps. However, it doesn't explicitly state when NOT to use this tool or provide clear alternatives among siblings like sls_diagnose_query.

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