agent-management

A set of commands for managing running AI agents, including listing them, inspecting their status, starting workers, assigning tasks, grouping them, resuming sessions, and stopping them.

In plain words
What is it for?
Use it to start and stop agents, inspect sessions, delegate assignments, send updates, organise groups, and verify completed work.
Why use it?
It provides one place to coordinate multiple agents and check that delegated work is progressing.

Skill for Claude CodeCodex

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.

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

Made for: Claude Code, Codex.

Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 518 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00056 $0.00518
Opus 5 $0.00028 $0.00259
Sonnet 5 $0.00011 $0.00104
Haiku 4.5 $0.00006 $0.00052

Measured yesterday against content hash ce846e43722d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-management 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 yesterday.

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.

skills/agent-management/SKILL.md · 49 lines

What it actually says

Agent Management

Use ai-devkit agent ...; if unavailable, use npx ai-devkit@latest agent ....

Workflow

  1. List agents: ai-devkit agent list --json.
  2. Identify self: compare your current session id to sessionId from list --json
  3. Inspect before acting: ai-devkit agent detail --id <name> --json --tail 20.
  4. Reuse idle agents when suitable; otherwise start one with agent start.
  5. Send self-contained assignments. Track each agent's task and last instruction.
  6. Verify completed work before reporting it done. Use $agent-communication for agent-to-agent updates.

Commands

ai-devkit agent list --json
ai-devkit agent detail --id <name> --json --tail 20
ai-devkit agent start --type codex --name <name> --cwd <path>
ai-devkit agent send --id <name> "<single-line instruction>"
ai-devkit agent send --id <name> --wait --timeout 120000 --json "<single-line instruction>"
ai-devkit agent send --group <group> "<single-line instruction>"
ai-devkit agent sessions --cwd <path> --type codex --json --limit 20
ai-devkit agent rename <old-name> <new-name>
ai-devkit agent kill <name>

Use exact names from list --json. Partial matches are convenient but risk sending work to the wrong agent.

Assignment Rules

  • Do not send instructions to yourself unless intentional.
  • Prefer task names like auth-review, ui-tests, or docs-pass.
  • Include objective, scope/files, constraints, validation command, expected output, and whether to stop or continue.
  • Assign non-overlapping files or sequence dependent work.
  • Use groups only for broadcasts that truly apply to every member.
  • Ask before killing agents you did not start, destructive actions, production/shared-system actions, or product decisions.

Example:

ai-devkit agent send --id auth-review "Review auth middleware in /repo. Do not edit files. Report security findings with file/line references, ranked by severity."
Files

What ships with it

1 file 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. yesterday First seen · 49 lines · 56 tokens per session scan A ce846e43722d

Subscribe to this mod's changes

agent-management is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,601 stars, last pushed 2d ago), licensed MIT. It adds 56 tokens to every session and 518 once invoked, about $0.0003 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.

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