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Anti Slop

Checked
rand·vlatest·other·MIT

Anti Slop reduces rambling responses by prioritizing concise answers, ensuring focused and efficient communication.

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 rand/cc-polymath --skill anti-slop -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

rand

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 rand/cc-polymath at baa2df1144.

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

Commit
baa2df1144
Manifest
skills/anti-slop/SKILL.md
Scanned
8 files, 2,688 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

The anti-slop skill helps AI agents produce more focused and relevant outputs by filtering out tangential or irrelevant information. It aims to reduce "slop" in responses, ensuring that the agent stays on topic and provides concise answers. This results in improved efficiency and clarity for users interacting with the agent.

When to use it

  • When an AI agent is generating overly verbose or rambling responses.
  • To ensure an agent focuses on specific tasks without getting sidetracked.
  • For agents that need to provide concise summaries of complex topics.
  • When dealing with creative writing prompts where maintaining a consistent theme is important.

Key capabilities

  • Filters tangential information
  • Reduces verbosity in responses
  • Maintains focus on the core topic
  • Provides more concise answers

Example prompts

  • "Summarize this article, but be very brief and avoid unnecessary details."
  • "Write a short story about [topic], keeping it tightly focused on the main character's journey."
  • "Explain [concept] in simple terms, without any extra background information."

Tips & gotchas

The skill’s effectiveness depends heavily on the clarity of the initial prompt. Providing specific instructions and constraints will yield better results.