Skip to content
TrustedSkillsbeta
Back to all skills

Performance Capacity Planning

Checked
kentoshimizu·vlatest·productivity·Apache-2.0

Helps with performance optimization, planning as part of agent workflows workflows.

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 kentoshimizu/sw-agent-skills --skill performance-capacity-planning -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

kentoshimizu

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.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned kentoshimizu/sw-agent-skills at 5b7bafb626.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
5b7bafb626
Manifest
skills/performance-capacity-planning/SKILL.md
Scanned
4 files, 89 lines
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.
What each check looks for →

About this skill

What it does

This skill enables AI agents to perform performance and capacity planning. It can analyze existing system metrics, predict future resource needs based on growth projections, and recommend adjustments to infrastructure or configurations. The goal is to ensure systems remain responsive and efficient under increasing load.

When to use it

  • Predicting Resource Needs: Before a major product launch or seasonal peak, estimate server capacity requirements.
  • Optimizing Existing Infrastructure: Identify bottlenecks and inefficiencies in current system performance.
  • Cost Optimization: Right-size cloud resources to avoid overspending on unused capacity.
  • Performance Troubleshooting: Diagnose the root cause of slow response times by analyzing resource utilization.

Key capabilities

  • Metrics analysis
  • Growth projection modeling
  • Resource recommendation generation

Example prompts

  • "Analyze our current server metrics and predict capacity needs for Q4."
  • "What are the potential bottlenecks in our database performance?"
  • "Recommend adjustments to our cloud infrastructure based on projected user growth over the next year."

Tips & gotchas

The accuracy of predictions depends heavily on the quality and completeness of historical data. Ensure sufficient metrics are available for reliable analysis.