agent-management

agent-management is a skill for Claude Code, Codex from autonomous-ai/autonomous-os. It costs 52 tokens per session (1,389 once invoked), scanned C, original, Apache-2.0.

A control interface for sending spoken tasks and follow-ups to coding or research agents running in a paired desktop application. It can target the selected project or work session and inspect or stop ongoing work.

In plain words
What is it for?
Use it to send voice instructions, address the currently selected worktree or agent session, review progress, stop work, and handle management notifications.
Why use it?
It lets you manage agent work from another device without guessing which terminal or project should receive a request. Retaining the session also keeps follow-up instructions with the same agent conversation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it to send voice instructions, address the currently selected worktree or agent session, review progress, stop work, and handle management notifications.

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Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-os/agent-management
Install

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.

Any agent
npx skills add autonomous-ai/autonomous-os --skill agent-management
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-os

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for agent-management

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/agent-management/github.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-os/agent-management)
Your own site
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/agent-management"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/agent-management/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-management

Your own site · 80×15
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/agent-management"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/agent-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,389 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.01389
Opus 5 $0.00026 $0.00694
Sonnet 5 $0.00010 $0.00278
Haiku 4.5 $0.00005 $0.00139

Measured today against content hash f94cf169c88c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade C, and why

agent-management scanned grade C with 1 finding 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 today.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/buddy_agents.py, scripts/voice_router.py, tests/test_buddy_agents.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Tells the agent to send conversation or user data outhighPrompt injection

An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.

`[agent-management]` notifications contain exact project/session IDs and completed/needs_input/error status. Briefly speak the actual result/question using the normal voice pipeline. Notifications **do not change** the r
skills/agent-management/SKILL.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent management

Use this only when the user explicitly asks to use Autonomous Buddy, a Buddy session, or its selected desktop pane. For ordinary requests to ask an agent on the paired Mac to perform work, including research, use harness-use; do not require a Buddy pairing as a fallback.

Run python3 scripts/buddy_agents.py from this skill directory on the Autonomous device. The localhost API is the device API, not the Mac. Never start the coding CLI or edit the desktop project's files on the lamp. Buddy owns the terminal PTY, worktree and provider conversation; Swift relays the paired WebSocket.

Spoken tasks and follow-ups

Use the voice action for normal conversation. Send JSON via stdin (quoted heredoc) to preserve spoken text without shell interpolation:

python3 scripts/buddy_agents.py voice - <<'JSON'
{"operation":"send","target":"active","request_id":"UNIQUE_UUID_FOR_THIS_TURN","prompt":"Add a test for reconnect after network loss"}
JSON
  • target:"active" (or its alias target:"current") explicitly addresses the worktree and focused pane selected inside Buddy. It does not guess from OS window focus, most recently updated session or terminal title. Use it for “current session”, “type to current session”, “agent/tab đang mở”, “session hiện tại”, “this selected agent”, or a request to switch to the currently selected tab. These explicit current-selection references override the retained voice target, even if the rest of the sentence says “it”. Fetch the live selection; do not substitute session IDs from conversation history. A plain shell pane cannot receive agent prompts.
  • Omit target (or use target:"previous") only for follow-ups such as “thêm test nữa” or “ask the same agent to continue”, without a current/selected-tab reference: the helper retains the last voice session even if desktop tab focus changes. On the first voice request with no retained context it uses Buddy's selected pane. A missing/closed/stale target is an error, never permission to choose another agent.
  • For an explicit project/session, call list and use the returned project_id and session_id. Named selectors project and worktree match exact returned names, IDs, branch names or paths; ambiguous matches return an error. Ask only which target is meant, then use those exact selectors. Do not invent Mac paths or IDs.
  • To create a session, use new_session:true plus provider:"codex" or "claude", and the requested target worktree. Example: {"operation":"send","target":"active","new_session":true,"provider":"codex","request_id":"UUID","prompt":"Fix reconnect"} creates in the selected worktree, including a feature worktree. Only create when the user asks to start a task/session; never create merely because a follow-up target is unavailable. If the provider is unspecified, ask which available agent to use.
  • operation:"select" retains an explicitly chosen session without sending a prompt. operation:"status" returns the target's session/events. operation:"stop" stops that target; it does not roll back edits.
  • conversation_id defaults to voice for the device's single spoken conversation. For a separate chat channel use its stable conversation identifier; do not share a voice target across unrelated chats or invent a new conversation ID on every turn. If a different speaker's target is uncertain, select explicitly.

Read the full file on GitHub · 49 lines

Files

What ships with it

4 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.

Changes

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.

  1. today Changed · +5 lines · -18 tokens per session f94cf169c88c
  2. yesterday First seen · 44 lines · 70 tokens per session scan C ed30dd2fff68

Subscribe to this mod's changes

agent-management is a skill published in the GitHub repository autonomous-ai/autonomous-os (317 stars, last pushed today), licensed Apache-2.0. It adds 52 tokens to every session and 1,389 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent to send conversation or user data out). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-08.