extract_nvbench

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

With all annotations false, the description carries the behavioral disclosure burden. It does add a useful constraint about the required artifact cardinality and sidecar declarations, which goes beyond a trivial restatement. However, it does not disclose side effects, failure behavior if the artifact constraint is violated, or whether extraction is repeatable, so transparency is partial.

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 two sentences with no filler. The first sentence states the exact purpose and source, and the second provides the essential artifact constraint. Every word contributes to operational understanding.

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 one-parameter extraction tool with an output schema, the description gives the core input condition and source context, which is helpful. It is incomplete, though, because it does not explain what happens when the artifact cardinality is violated, what output is produced beyond the schema, or how this relates to sibling extraction flows. It is adequate but leaves clear 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?

Schema description coverage is 0%, so the description must compensate for the undocumented run_id parameter. The phrase 'The run must contain...' references the run concept, but it never explicitly states that run_id identifies the preserved bundle to extract from. The single parameter's meaning is left mostly to its title 'Run Id,' with no added semantic guidance in the description.

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 opens with a specific verb and resource: 'Extract NVBench sample times and frequencies from a preserved bundle.' It clearly identifies the artifact type (NVBench JSON) and distinguishes this from sibling extract_* tools that target other artifacts like pytest, memray, or perfetto. The primary NVBench artifact requirement further narrows the purpose.

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 a clear precondition: the run must contain exactly one primary NVBench JSON artifact and zero or more declared sidecars. This implies the tool is for extraction from a preserved bundle, but it does not explicitly name alternatives or state exclusions such as 'use import_nvbench if the bundle is not preserved.' Usage context is present but not fully elaborated.

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