Dispatching Parallel Agents
CheckedDavila7's dispatching skill efficiently launches and manages multiple parallel agents for complex task decomposition and accelerated execution.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add davila7/claude-code-templates --skill dispatching-parallel-agents -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
davila7
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.
Automated safety checks
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 davila7/claude-code-templates at 79182c51fb.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 79182c51fb
- Scanned
- 2 files, 346 lines
- Copies in repo
- 2 — all of them scanned
About this skill
What it does
This skill orchestrates multiple AI agents to work simultaneously on distinct subtasks, enabling complex workflows that require concurrent processing. It allows a single user prompt to trigger a coordinated team of specialized agents rather than relying on a linear, single-agent execution model.
When to use it
- You need to process large datasets where different sections can be analyzed independently and in parallel.
- Your workflow involves distinct phases (e.g., research, coding, testing) that benefit from running concurrently to reduce total wait time.
- You are managing a project requiring diverse expertise, such as generating code while simultaneously writing documentation or running unit tests.
- You want to simulate a human team environment where multiple specialists collaborate on a single objective without sequential handoffs.
Key capabilities
- Parallel Execution: Launches multiple agent instances at once instead of waiting for one to finish before starting the next.
- Task Decomposition: Automatically breaks down complex user requests into independent subtasks suitable for concurrent handling.
- Coordinated Output: Aggregates results from all running agents into a unified response or deliverable.
- Resource Optimization: Maximizes throughput by utilizing available compute resources efficiently across multiple tasks.
Example prompts
- "Analyze the attached sales report, generate a Python script to visualize the data, and draft an executive summary email simultaneously."
- "Run unit tests on this codebase while also refactoring the legacy functions and updating the README documentation in parallel."
- "Research three different approaches to solving this optimization problem, implement the best one, and write a tutorial post about it all at once."
Tips & gotchas
Ensure your task definition clearly separates independent subtasks; overlapping dependencies may cause agents to conflict or wait unnecessarily. Monitor token usage closely, as spawning multiple agents simultaneously can consume resources faster than sequential execution.