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Beads Workflow

Checked
dicklesworthstone·vlatest·other

Automates complex data processing pipelines using configurable bead-like modules for repeatable workflows.

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 dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations --skill beads-workflow -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

dicklesworthstone

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 dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations at 4d332440c3.

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

Scanned
4 files, 657 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

The beads-workflow skill provides a mechanism for managing and executing specific workflow sequences within an AI agent environment, though its exact operational logic is not detailed in the available source data. It serves as a foundational component for organizing complex tasks or automating repetitive processes within the broader agent_flywheel_clawdbot_skills_and_integrations suite.

  • Automating multi-step task execution sequences

  • Integrating with the ClawDB bot ecosystem

  • Structuring agent behavior through defined workflows

  • Enhancing operational efficiency in automated environments

  • Workflow orchestration capabilities

  • Integration support for AI agents

  • Task sequencing management

"Execute a new workflow sequence using beads-workflow." "List available workflow configurations in the current environment." "Trigger the beads workflow to process incoming data batches."

To effectively utilize this skill, ensure your agent is properly connected to the underlying ClawDB infrastructure. Since specific implementation details are not provided in the source, verify compatibility with your specific AI agent framework before deployment.