performance-profiler
- Repo stars 1
- Author updated Live
- Author repo claude-skills
- Domain
- Engineering
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @00PrabalK00 · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: performance-profiler
description: Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks…
category: engineering
runtime: no special runtime
---
# performance-profiler output preview
## PART A: Task fit
- Use case: Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks, and code hotspots. Use when an app is slow or a performance budget is being missed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Core Workflow / Deliver” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks, and code hotspots. Use when an app is slow or a performance budget is being missed.”.
- **02** When the source has headings, the agent prioritizes “Overview / Core Workflow / Deliver” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Validate with a small run
Start with a small task and check whether the result follows “Overview / Core Workflow / Deliver”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: performance-profiler
description: Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks…
category: engineering
source: 00PrabalK00/claude-skills
---
# performance-profiler
## When to use
- Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks, and code hotspots. Use…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Overview / Core Workflow / Deliver” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "performance-profiler" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Overview / Core Workflow / Deliver
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Performance Profiler
Overview
Identify hot paths, bottlenecks, and likely performance wins from profiles, traces, benchmarks, and code hotspots.
Core Workflow
- Gather the smallest high-signal evidence set: failing outputs, logs, configs, recent changes, and relevant runtime context.
- Inspect the implementation and surrounding setup to isolate the narrowest plausible failure surface.
- Rank likely causes, rule out weak explanations, and identify the most actionable next fix or experiment.
- Validate the explanation with the smallest reliable check the repo or environment supports.
Deliver
- A concise diagnosis with the most likely root cause or bounded uncertainty.
- The highest-signal evidence and suspect files, configs, or systems involved.
- The smallest safe fix path or next experiment to run.
Guardrails
- Do not claim a root cause without evidence that explains the observed behavior.
- Separate symptoms from likely causes and call out uncertainty explicitly.
- Prefer the smallest reproducible scope before escalating to broad changes.
- Prefer repository evidence, command output, and nearby tests over vague intuition.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review