CLI Agent Orchestrator is a tool that coordinates multiple AI coding command-line programs by running them as separate workers in isolated terminal sessions. A supervisor uses it to delegate software tasks to specialist agents in parallel or in sequence while the workers retain their normal command-line capabilities. The catalogue skills operate this orchestration workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/awslabs/cli-agent-orchestrator/cao-pluginnpx skills add awslabs/cli-agent-orchestrator --skill cao-plugingit clone --depth 1 https://github.com/awslabs/cli-agent-orchestratorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/awslabs/cli-agent-orchestrator/cao-plugin)<a href="https://agentmods.dev/skills/awslabs/cli-agent-orchestrator/cao-plugin"><img src="https://agentmods.dev/badge/skills/awslabs/cli-agent-orchestrator/cao-plugin.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00096 | $0.02852 |
| Opus 5 | $0.00048 | $0.01426 |
| Sonnet 5 | $0.00019 | $0.00570 |
| Haiku 4.5 | $0.00010 | $0.00285 |
Grade A, and why
cao-plugin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CAO Plugin Creator
Guide for creating a new CAO plugin. A "plugin" is a Python package installed alongside CAO that subscribes to CAO lifecycle and messaging events via typed async hooks.
What You're Building
A CAO plugin is a standalone Python package that:
- Subclasses
CaoPluginfromcli_agent_orchestrator.plugins - Registers async hook methods with
@hook("<event_type>")decorators - Is discovered via the
cao.pluginsPython entry-point group atcao-serverstartup - Runs fire-and-forget — plugin exceptions are caught and logged as warnings, never propagated back into CAO
Typical uses: forwarding inter-agent messages to chat apps, logging/observability, external dashboards, metrics export, alerting on session or terminal lifecycle.
Before You Start
Gather this information:
- Which events do you need? See
references/hook-events.mdfor the full catalog. - Does the plugin need persistent state across events? (HTTP client, DB connection, buffer) — if so, use
setup()/teardown(). - How is it configured? v1 has no injected config API — read env vars in
setup(), optionally viapython-dotenv. - What are the failure semantics of your integration? Remember CAO swallows hook exceptions — you must decide whether to log, retry, or drop on your own.
Hard Requirements
These are the non-negotiable contracts a plugin must satisfy to be loaded and dispatched to. Verify each one before calling your plugin complete.
1. Package layout
Minimum viable layout:
my-cao-plugin/
├── pyproject.toml # Build config + entry-point declaration
├── my_cao_plugin/
│ ├── __init__.py # Can be empty
│ └── plugin.py # Contains the CaoPlugin subclass
├── tests/ # Optional but strongly recommended
│ └── test_plugin.py
├── env.template # Optional; only if the plugin reads env vars
└── README.md # Optional; install + config instructions for users
See examples/plugins/cao-discord/ in this repo for a complete reference implementation.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 265 lines · 96 tokens per session scan A 6a3a30b9c8d7
cao-plugin is a skill published in the GitHub repository awslabs/cli-agent-orchestrator (1,201 stars, last pushed yesterday), licensed Apache-2.0. It adds 96 tokens to every session and 2,852 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
tool-selection
Internal guidance for choosing between agent-rack's sync and background execution tools, and when to use per-agent shortcuts. Use whenever delegating a task to a claude/codex/opencode/Antigravity/custom sub-agent through agent-rack.
review
Run a structured, read-only code review through agent-rack's agentreview tool.
session-send
Send follow-up input to a running background agent-rack session.
review-handling
Internal guidance for presenting agent-rack's agentreview output back to the user. Use whenever an agentreview call (foreground or via agentsessionstatus) returns a result.
session-logs
Read the raw stdout/stderr event stream from a background agent-rack session.
session-start
Start a background sub-agent session via agent-rack for a long-running task.