profile_page_performance

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

With no annotations, the description carries full responsibility for behavioral disclosure, and it does so thoroughly. It states side effects: 'may temporarily disable cache ('disable_cache' defaults to false); impacts page memory/CPU.' It also mentions prerequisites: 'requires an active Chrome tab' and background bandwidth usage. It discloses the return format: 'JSON with vitals, blocking time, and top 5 long tasks.' This is comprehensive for a tool with no annotations.

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 compact and well-structured. It front-loads the primary purpose, then efficiently covers side effects, prerequisites, return format, usage scenarios, and alternatives in a few sentences. Every clause contributes meaningful information—no filler or redundancy.

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?

Despite having 5 parameters and no output schema, the description covers everything an agent needs to call the tool correctly: what it does, when to use it, side effects, prerequisites, return structure, and parameter interactions. The parameter details are in the schema, so the description compensates well for the lack of an output schema by specifying the JSON contents.

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 the schema already documents each parameter. However, the description adds meaningful interaction context beyond the schema: e.g., 'when true with action='reload', simulates cold start; cache restored after profiling' for disable_cache, and 'use 3000-5000 for typical pages' for duration_ms. This adds value beyond the schema's basic descriptions.

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: 'Records a performance trace of page execution, calculating Core Web Vitals (FCP, LCP, DCL, Load) and identifying Long Tasks (>50ms blocking).' It specifies a concrete action (records), resource (performance trace), and the specific metrics, which distinguishes it from sibling tools like get_performance_metrics that likely fetch existing metrics rather than record a fresh trace.

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 gives explicit usage context: 'Use this to optimize performance, identify bottlenecks, measure cold starts.' It also names alternatives: 'Alternatives: browser DevTools Performance tab, real user monitoring (RUM).' This tells the agent when to use it and what other approaches exist, though it doesn't explicitly state when NOT to use it, which is a minor gap.

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