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Parallel Agents

Checked
hainamchung·vlatest·agents·MIT

Orchestrates multiple parallel agents from hainamchung to rapidly explore solutions and optimize complex tasks.

Repository

Install on your platform

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

Installs under a different name. Its SKILL.md names it dispatching-parallel-agents, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add hainamchung/agent-assistant --skill dispatching-parallel-agents -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

hainamchung

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 hainamchung/agent-assistant at 89cb983bb4.

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

Commit
89cb983bb4
Manifest
skills/dispatching-parallel-agents/SKILL.md
Scanned
1 file, 126 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 you to manage and coordinate multiple AI agents simultaneously. It enables splitting complex tasks into smaller, manageable pieces handled by different specialized agents, then aggregating their results for a comprehensive outcome. The skill facilitates running these agents in parallel to significantly reduce overall processing time.

When to use it

  • Complex research projects: Delegate sections of a literature review or data analysis to separate agents and combine findings.
  • Content creation workflows: Have one agent draft content, another edit it, and a third optimize for SEO – all concurrently.
  • Code generation & testing: Assign different agents to generate code modules, run unit tests, and perform integration checks in parallel.
  • Data processing pipelines: Split large datasets into chunks and have multiple agents process them simultaneously before merging the results.

Key capabilities

  • Parallel agent execution
  • Task splitting and delegation
  • Result aggregation from multiple agents
  • Workflow orchestration across agents

Example prompts

  • "Run Agent A to summarize this document, Agent B to extract key entities, and Agent C to translate it into French – all at the same time."
  • "Divide this coding task into three parts: design, implementation, and testing. Assign each part to a different agent and combine their outputs."
  • “Process these 1000 images using Agent X for object detection and Agent Y for image enhancement in parallel.”

Tips & gotchas

To ensure optimal performance, clearly define the roles and responsibilities of each agent before initiating parallel execution. The effectiveness depends on well-defined tasks suitable for independent agent handling.