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Create Plan

Checked
mhylle·vlatest·productivity·MIT

Helps with creation, 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 mhylle/claude-skills-collection --skill create-plan -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

mhylle

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 mhylle/claude-skills-collection at 20dadb5578.

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

Commit
20dadb5578
Manifest
skills/create-plan/SKILL.md
Scanned
2 files, 472 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 allows an AI agent to generate plans based on user requests. It can outline steps, suggest resources, and organize tasks for achieving a specific goal. The generated plan is designed to be actionable and provide clear direction for users.

When to use it

  • Planning a complex project: Break down large projects into manageable steps with timelines and resource suggestions.
  • Organizing travel itineraries: Generate detailed day-by-day plans including transportation, activities, and accommodation.
  • Creating study schedules: Develop structured learning plans with specific topics, deadlines, and recommended materials.
  • Outlining event logistics: Plan events by outlining tasks like venue selection, catering, invitations, and scheduling.

Key capabilities

  • Plan generation
  • Task outlining
  • Resource suggestion
  • Actionable steps

Example prompts

  • "Create a plan for learning Python programming."
  • "Generate an itinerary for a 5-day trip to Paris."
  • "Outline the steps needed to organize a fundraising event."

Tips & gotchas

The quality of the generated plan depends heavily on the clarity and specificity of the initial prompt. Providing detailed context and desired outcomes will yield more useful results.