sentinel_logs_search_with_dummy_data

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 states the tool tests queries with mock data and validates KQL locally, which implies a read-only, non-destructive operation, but doesn't clarify permissions, rate limits, or what 'locally' entails (e.g., no network calls). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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 highly concise and front-loaded, consisting of a single sentence that efficiently conveys the core functionality: 'Test a KQL query with mock data using a datatable. Validates KQL locally first.' Every word earns its place, with no wasted text or redundancy, making it easy 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 of a query-testing tool with 1 parameter, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on parameter usage, behavioral traits (e.g., error handling, mock data scope), and output format. While concise, it doesn't provide enough context for an agent to use the tool effectively without additional assumptions.

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 input schema has 1 parameter ('kwargs') with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'kwargs' should contain (e.g., the KQL query string, datatable configuration, or validation options). With low schema coverage, the description fails to compensate, leaving the parameter's meaning and usage unclear.

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: 'Test a KQL query with mock data using a datatable. Validates KQL locally first.' It specifies the verb ('test'), resource ('KQL query'), and method ('with mock data using a datatable'), making the purpose unambiguous. However, it doesn't explicitly differentiate from its sibling 'sentinel_logs_search' or other query-related tools, which prevents 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 mentions 'validates KQL locally first,' which implies a testing or validation context, but doesn't specify when to choose this over 'sentinel_logs_search' (for real data) or 'sentinel_query_validate' (for validation without mock data). Without explicit usage context or exclusions, the agent lacks clear direction.

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