fleet

fleet is a skill for Claude Code, Codex from brizzai/fleet. It costs 133 tokens per session (2,697 once invoked), scanned A, original, Apache-2.0.

A command-line tool for running several coding-agent sessions at the same time, each in its own tmux session and usually its own Git worktree, which is a separate working copy of a repository.

In plain words
What is it for?
Use it to start agents on separate features, long refactors, or test investigations, then send messages or check their progress.
Why use it?
It lets independent tasks run in the background without competing for the files in your current working copy.

Skill for Claude CodeCodex

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

Good fit Use it to start agents on separate features, long refactors, or test investigations, then send messages or check their progress.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/brizzai/fleet/skill
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 brizzai/fleet --skill skill
Clone the repo
git clone --depth 1 https://github.com/brizzai/fleet

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 fleet

README.md
[![agentmods](https://agentmods.dev/badge/skills/brizzai/fleet/skill/github.svg)](https://agentmods.dev/skills/brizzai/fleet/skill)
Your own site
<a href="https://agentmods.dev/skills/brizzai/fleet/skill"><img src="https://agentmods.dev/badge/skills/brizzai/fleet/skill/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 fleet

Your own site · 80×15
<a href="https://agentmods.dev/skills/brizzai/fleet/skill"><img src="https://agentmods.dev/badge/skills/brizzai/fleet/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 133 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,697 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Excessive Agency · line 78
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
How audits are shown
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 $0.00133 $0.02697
Opus 5.5 $0.00053 $0.01079
Sonnet 5.5 $0.00027 $0.00539
Haiku 4.5 $0.00013 $0.00270

Measured 9d ago against content hash 148a99d17b80, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fleet 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 9d 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.

internal/skill/SKILL.md · 217 lines

How it starts

The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.

fleet

fleet runs coding-agent sessions in parallel, each in its own tmux session and — unless you point it at an existing directory — its own git worktree. From a shell you can create one, hand it a task, see what it and every other session is doing, answer its prompts, and collect its result.

Run fleet <command> --help for the exact flags. This file covers when and how to reach for them.

When to hand work to a session

Spawn a session when the work is independent of the current turn and would otherwise block it: a second feature, a long refactor, a flaky-test hunt, an issue that just needs doing. The session gets its own worktree, so it can't collide with the tree you're editing.

Do the work inline instead when it's part of what the user asked for right now, or when it touches files being edited in this conversation.

Say which session you started and what you gave it. The user drives fleet's TUI and needs to know a new row appeared.

Start a session on a task

fleet wt <branch> -p "<the task, phrased as you would to another agent>"

Creates the worktree, starts the agent, and delivers the prompt as its first message, so the session opens already working on it. -p accepts multi-line text and text starting with -.

Pipe a task in from another tool with -p -, which reads stdin:

gh issue view 242 | fleet wt fix-242 -p -

Worth knowing:

  • --base <branch> branches from something other than the repo's default branch.
  • --path <repo> picks the repo (defaults to cwd). It resolves to the repo's main worktree, so running it from inside one worktree doesn't nest names.
  • --agent claude|codex|opencode|copilot overrides the user's configured default agent.
  • --account <email> picks which Claude subscription the session bills to. Claude only — passing it with another agent is an error, not a silent no-op.
  • --ticket BRZ-3182 materializes a Linear issue (description, comments, screenshots) into the worktree and names the branch from it. Conflicts with -p.
  • --no-session makes only the worktree and prints its path, so it composes: cd "$(fleet worktree scratch --no-session)".
  • --model / --effort — see below.

Read the full file on GitHub · 217 lines

Files

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.

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. 9d ago Changed · +76 lines · +29 tokens per session 148a99d17b80
  2. 25d ago Changed · +3 tokens per session 51db567427bf
  3. 2mo ago First seen · 141 lines · 101 tokens per session scan A 9c939de582b8

Subscribe to this mod's changes

fleet is a skill published in the GitHub repository brizzai/fleet (59 stars, last pushed 9d ago), licensed Apache-2.0. It adds 133 tokens to every session and 2,697 once invoked, about $0.0005 per session on Opus 5.5. 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.