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theSharque
by theSharque

profile_time

Analyze CPU time from a .jfr file using bottom-up aggregation to identify methods consuming the most CPU and find performance bottlenecks.

Instructions

CPU time (bottleneck) profile from a .jfr file. Uses bottom-up aggregation: each method is counted in every sample where it appears in the stack, including time spent in callees. Returns methods consuming the most CPU time. Use when the goal is to find performance bottlenecks and slow code paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathNoPath to .jfr file. Shortcuts: 'new_profile' (current, default) or 'old_profile' (previous). Or full path e.g. recordings/new_profile.jfr.new_profile
topNNoMaximum number of top methods by CPU time to return. Default: 10.
Behavior4/5

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

Discloses bottom-up aggregation behavior where each method is counted in every sample including callee time. No annotations provided, so description carries full burden; it provides sufficient transparency for a read-only profiling tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences are concise and well-structured: first defines purpose and behavior, second provides usage guidance. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description clarifies returns methods consuming most CPU time. Lacks specifics on output format (e.g., values, sorting), but the tool's purpose is clear given context and sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so description adds limited value beyond schema. It implies topN limits the number of methods returned, but doesn't provide new semantic detail beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool profiles CPU time from a .jfr file using bottom-up aggregation. It specifies the resource (.jfr file) and action (profile CPU time), distinguishing it from sibling profiling tools like profile_frequency or profile_memory.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises use when finding performance bottlenecks and slow code paths. While it doesn't mention when not to use or list alternatives, the guidance is clear and contextually appropriate.

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

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