build_logql_query

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'suggestions,' implying advisory or interactive behavior, but doesn't clarify if this is a read-only helper, whether it requires specific permissions, what the output format is, or any rate limits. For a tool with no annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids redundancy and wastes no words, making it easy for an agent to parse quickly.

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 complexity (5 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral traits, usage context, and output expectations. While the schema covers parameters, the description doesn't compensate for missing annotations or provide enough context for effective tool invocation in a multi-tool environment.

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 100%, meaning all parameters are documented in the schema itself. The description adds no additional semantic context about parameters beyond what's in the schema (e.g., it doesn't explain how 'labels' and 'filter' interact or provide examples of query building). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

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: 'Help build a LogQL query with suggestions for log stream selectors and filters.' It specifies the verb ('build'), resource ('LogQL query'), and scope ('log stream selectors and filters'). However, it doesn't explicitly differentiate from sibling tools like 'query_loki' or 'build_prometheus_query', which would be needed for a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'query_loki' (which likely executes queries) or 'build_prometheus_query' (for Prometheus queries), nor does it specify prerequisites or exclusions. This leaves the agent without context for tool selection.

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