profiler-cpu-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. It discloses a crucial sampling behavior (self-times are summed sampling intervals and do not change when widening a window), states that every table shows covered samples and idle fraction, and notes the fatal failure condition. This goes well beyond a generic description.

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 front-loaded with the purpose and prerequisite, then presents modes in a compact bullet-style list, adds the nuanced sampling explanation, and ends with a usage hint and failure condition. Every sentence adds value; no fluff.

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 complex tool with 8 parameters, no output schema, and no annotations, the description is remarkably complete: it explains modes, parameter roles, return format ('markdown table'), preconditions, and failure behavior. The subtle sampling caveat fills a gap that could mislead users into thinking wider windows increase data.

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% and the schema provides detailed per-parameter descriptions. However, the description adds extra semantic context for key parameters beyond the schema: it explains the meaning of time_window_ms (the clock reference 'same clock profiler-commit-query prints') and connects function_name/component_name to their modes. Slight deduction because not every parameter is explicitly tied to a mode in the description (port, top_n), but the schema covers those.

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 a specific verb ('Query') and resource ('Hermes CPU profile data'), enumerates the four modes (top_functions, time_window, call_tree, component_cpu), and explains what each returns. It clearly distinguishes from sibling profiler tools by scoping to CPU ('CPU profile data', 'CPU hotspots') vs the react-profiler-* / native-profiler-* / profiler-commit-query / profiler-stack-query siblings.

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?

Explicitly states when to use ('Use when investigating JS CPU hotspots or correlating CPU cost with specific components') and names the required prerequisite ('Requires react-profiler-stop (and ideally react-profiler-analyze) to have been called first'). It also warns of failure mode if the prerequisite is not met ('Fails if no CPU profile is stored — run react-profiler-stop first').

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