Agent Manager Skill
CheckedDavila7's agent-manager-skill orchestrates multiple AI agents to achieve complex goals through task delegation and progress monitoring.
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 agent-manager-skill -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
- 1 file, 37 lines
About this skill
What it does
The agent-manager-skill enables users to efficiently manage multiple AI agents, including creating, configuring, and monitoring their performance. It provides tools for organizing workflows, assigning tasks dynamically, and tracking the status of each agent in real time.
When to use it
- Managing a team of AI agents working on different parts of a complex project.
- Automating repetitive tasks across multiple agents with centralized control.
- Monitoring agent performance and adjusting configurations on the fly.
- Scaling operations by dynamically adding or removing agents as needed.
Key capabilities
- Create and configure multiple AI agents in one interface.
- Assign and prioritize tasks across agents.
- Monitor real-time status and logs of each agent.
- Scale agent numbers based on workload demands.
Example prompts
- "Assign the data analysis task to Agent 3 and track its progress."
- "Scale up the number of agents handling customer support requests."
- "Show me a summary of all active agents and their current status."
Tips & gotchas
- Ensure your system meets the minimum resource requirements for running multiple agents simultaneously.
- Use clear task definitions to avoid conflicts when assigning work across agents.