extract_kernel_validation

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

Annotations provide no safety profile (all hints are false), and the description does not disclose side effects, prerequisites, or whether extraction mutates state. The term 'Extract' suggests read-only, but readOnlyHint=false implies potential non-read behavior without explanation.

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, front-loaded sentence with no filler or redundant content. Every word earns its place, and it is appropriately concise for a one-parameter extraction tool.

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?

Although an output schema exists and parameter count is low, the description omits essential context such as what 'bounded per-case metrics' means, how to obtain run_id, and when this extractor is appropriate. With many sibling extract tools, this minimalism leaves significant gaps.

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 only parameter, run_id, is left unexplained; the description does not clarify what it identifies or how it relates to kernel-validation evidence. Schema coverage is 0%, and the description fails to add meaning beyond the basic type/length 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 states the tool extracts bounded per-case metrics specifically from kernel-validation v1 evidence, using a specific verb and resource. It distinguishes itself from sibling extract tools (e.g., extract_inference_trace, extract_perfetto) by naming the 'kernel-validation' domain.

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?

No guidance is provided about when to use this tool over alternatives or any exclusions. While the name implies kernel-validation context, there is no explicit mention of when to select this extractor versus other extract_* sibling tools.

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