profiler-cpu-query

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

Since no annotations are provided, the description carries full burden. It discloses that the tool returns a markdown table, fails if no profile is stored, and describes each mode's behavior. It implies read-only access by being a query tool. However, it does not mention potential side effects, rate limits, or auth requirements, but these are not critical for a CPU query tool.

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 appropriately sized and front-loaded with the purpose. It has a clear structure: introduction, prerequisites, mode list with explanations, usage guidance, and failure condition. Every sentence adds value, though it could be slightly more concise without losing clarity.

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 no output schema, the description mentions returns a markdown table but does not detail the format for each mode. It does not clarify how top_n applies to non-top_functions modes. The time_window_ms object is described in schema but not elaborated in description. For 8 parameters and multiple modes, the description is adequate but leaves some behavioral details implicit.

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 coverage is 100%, so baseline is 3. The description adds value by grouping parameters with modes (e.g., function_name for call_tree, component_name for component_cpu) and explaining the time_window_ms nested object context. It provides usage context that the schema alone does not, such as the effect of include_callers in call_tree mode.

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 it queries Hermes CPU profile data with targeted modes for iterative investigation. It lists four specific modes (top_functions, time_window, call_tree, component_cpu) with their purposes, making the tool's function and scope immediately clear. It distinguishes itself from sibling tools like profiler-commit-query and profiler-stack-query by focusing on CPU profiling.

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 explicitly states prerequisites: 'Requires react-profiler-stop (and ideally react-profiler-analyze) to have been called first' and 'Fails if no CPU profile is stored — run react-profiler-stop first'. It also indicates when to use the tool: 'Use when investigating JS CPU hotspots or correlating CPU cost with specific components.' While it does not explicitly list when not to use it versus alternatives, the mode descriptions provide sufficient context.

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