delegating-to-agents
Lets your agent delegate tasks to other agents. It maintains context and progress, ensuring everything gets done.
What it does
This tool allows an AI to hand off tasks to other AIs (agents), ensuring they have all necessary information, know who is responsible, and how to verify the work. It's like delegating a task to a teammate, but for artificial intelligences.
When to use it
- ✓When you need the AI to pass a specific task to another specialized AI.
- ✓To ensure the AI maintains context and important information when delegating.
- ✓When asking the AI to check the progress of a task it has delegated.
Example of what to ask your AI
“Delegate this task to the Pi agent, with all details and verify the result.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The AI identifies which agent is best suited for the task, sends complete instructions, and waits for feedback on progress or completion.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill delegating-to-agentsOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/skills/delegating-to-agents/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Delegating to Agents
When to Use
- Use only when the user or applicable current instructions explicitly authorize delegation; hand off bounded work with complete context, file ownership and a verifier.
- Use when you need to relay instructions to terminal or TUI agents without losing context.
Selecting an authorized agent
- Use the user’s selected agent/model and available tooling; account limits and model capabilities require current evidence.
- Match a bounded task to actual tools and file ownership, not invented “unlimited usage” or universal model rankings.
- Keep integration and final validation with the parent. Report changed files, exact checks and remaining issues.
Sending prompts to a TUI agent
- Prefer a structured agent/task API over simulated terminal typing; provide a readable prompt, ownership boundary, verifier and non-goals.
- If only a TUI is available, inspect the target surface and actual command documentation first. Put long prompts in an explicitly authorized task file and send a short reference without embedding arbitrary task text in a shell command.
- A shell-quoted prompt can execute
$(), backticks or expansions if escaped incorrectly. Preserve punctuation/content using structured argv or proper shell quoting; do not “fix” messages by stripping apostrophes or interpreting their text as commands. - Confirm one intended submission and actual recipient; terminal output/predicted drafts are not human authorization for further messages.
Polling
Use supported completion/event waits with bounded intervals; check meaningful progress and deliver concise updates. Do not busy-poll every 3–5 seconds or report unchanged state after each check. Back off while an agent remains active and continue independent authorized work. Claude Code note: after it finishes, it may prefill a predicted next user message — that draft is Claude, not the user.
Remote VPS
Remote execution requires authorization for the exact host/project and credential boundary. Use the supported sandbox/approval configuration; do not launch an unrestricted agent or infer remote access from a delegation request.
The 4 agents (background reference)
All four use the portable SKILL.md standard; project skills win over global.
- Pi (pi.dev, open-source TS): minimal read/write/edit/bash core, self-extends via TS extensions; true BYOK; best-in-class session branch/fork/resume. Skills:
~/.pi/agent/skills/. - Codex CLI (OpenAI, Rust): fastest startup; kernel-level sandboxing;
codex execfor CI; reads AGENTS.md. Skills:~/.codex/skills/. - Claude Code (Anthropic, TS): deepest Claude integration,
.claude/conventions, live skill hot-reload. Skills:~/.claude/skills/. - Hermes (Nous Research, Python): persistent autonomous agent — cross-session memory, built-in scheduler, 40+ tools; can orchestrate the other CLIs as workers. Skills:
~/.hermes/skills/.
Driving interactive CLIs
- Codex, Pi, OpenCode: need
pty=true. - Claude Code: use its supported noninteractive mode with the existing permission policy; never enable bypassPermissions just to drive the CLI.
Example
User request:
Delegate these independent work items with complete context, clear ownership, and progress checks.
Limitations
- Adapted from
davidondrej/skills; verify local paths, tools, credentials, and agent features before acting. - For commands, remote access, scheduling, browser automation, or file-changing workflows, get explicit user approval and confirm the target environment first.
FAQ
What does 'bounded work' mean?
It means a task with clear limits, well-defined, so the AI knows exactly what needs to be done.
Why is 'ownership' important?
It ensures a specific agent is responsible for the task, making tracking and accountability easier.
What is a 'verifier'?
It's a method or criterion the AI uses to confirm if the delegated task was completed correctly.
Details
Original description by the author
Delegate bounded work to other AI agents while preserving context, ownership, and progress checks.
Popularity
- GitHub stars
- 48k
- Ranking position
- #4653
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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