react-profiler-analyze

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

With no annotations, the description fully bears the burden of transparency. It details the output structure, that raw data is saved to disk for later reload via profiler-load, the report's focus on hot commits, and the prerequisite of react-profiler-stop. It also explains the annotations parameter's calculation. No contradictions exist.

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 well-structured and front-loaded: first sentence states purpose and output, followed by report structure, annotations explanation, prerequisites, and usage flow. At around 180 words, it is concise but could slightly reduce repetition (e.g., offsetMs explanation appears twice). Still, it efficiently conveys all necessary information.

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 tool's complexity (6 parameters, no output schema, multiple sibling tools), the description is highly complete. It covers prerequisites, output shape, report structure, failure conditions, workflow after report, and relationship to other tools. The absence of an output schema is compensated by detailing the return fields. No gaps remain.

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 thoroughly explaining the 'annotations' parameter, including how to compute offsetMs using other tool outputs (tap/swipe and react-profiler-start). For other parameters, it largely repeats schema descriptions but provides helpful context (e.g., linking device_id to debugger-connect). This additional guidance justifies a score above baseline.

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: 'Analyze stored profiling data and return a markdown performance report.' It specifies the output fields and report structure, and distinguishes itself from sibling tools by outlining the workflow and mentioning related profiler tools for drill-down, such as profiler-cpu-query and profiler-commit-query.

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 explicit usage guidance: 'Use when the profiling session is complete and you need to interpret the collected data.' It states the prerequisite ('Requires react-profiler-stop to have been called first'), describes the post-report workflow (ask user about further investigation), and explains how to compute the optional annotations parameter. It also mentions failure conditions, offering complete usage context.

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