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Response Time Analyzer

Listed
jeremylongshore·vlatest·backend·MIT

Analyzes API responses to pinpoint latency issues and optimize performance for faster application speeds.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill response-time-analyzer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

The Response Time Analyzer skill assesses the speed of responses from various AI agents. It provides metrics like average response time, latency distribution, and identifies potential bottlenecks in agent performance. This allows for optimization of prompts and agent configurations to improve overall efficiency.

When to use it

  • Debugging slow agent interactions: Investigate why an agent is taking longer than expected to respond to requests.
  • Comparing different AI agents: Evaluate the relative speed and responsiveness of multiple AI models or agent implementations.
  • Optimizing prompt design: Determine if changes to prompts are impacting response times positively or negatively.
  • Identifying system bottlenecks: Pinpoint areas in your workflow where delays are occurring, such as API calls or data processing steps.

Key capabilities

  • Measures average response time.
  • Provides latency distribution analysis.
  • Identifies potential performance bottlenecks.

Example prompts

  • "Analyze the response time of Agent X when answering questions about historical events."
  • "Compare the response times of Agent A and Agent B for a series of coding tasks."
  • "Evaluate how changes to prompt length affect the average response time of this agent."

Tips & gotchas

The accuracy of the analysis depends on consistent prompting and controlled testing conditions. Ensure you are using similar prompts and input data when comparing different agents or configurations.