AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent 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/ufy2024/auc/claude-devfleetnpx skills add ufy2024/AuC --skill claude-devfleetgit clone --depth 1 https://github.com/ufy2024/AuCWrote 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/ufy2024/auc/claude-devfleet)<a href="https://agentmods.dev/skills/ufy2024/auc/claude-devfleet"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/claude-devfleet.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 5.1 | $0.00036 | $0.01549 |
| Opus 5 | $0.00018 | $0.00775 |
| Sonnet 5 | $0.00007 | $0.00310 |
| Haiku 4.5 | $0.00004 | $0.00155 |
Grade A, and why
claude-devfleet 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 2d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- claude-devfleet — 94% identical, 46 lines differ
- claude-devfleet — 94% identical, 27 lines differ
- claude-devfleet — 92% identical, 28 lines differ
- claude-devfleet — 92% identical, 37 lines differ
- claude-devfleet — 92% identical, 28 lines differ
- claude-devfleet — 92% identical, 38 lines differ
- claude-devfleet — 92% identical, 37 lines differ
- gemini-devfleet — 91% identical, 45 lines differ
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude DevFleet Multi-Agent Orchestration
When to Use
Use this skill when you need to dispatch multiple Claude Code agents to work on coding tasks in parallel. Each agent runs in an isolated git worktree with full tooling.
Setup
The DevFleet server is a separate project, not bundled with ECC. Install and run it from its repository first: https://github.com/LEC-AI/claude-devfleet
Then connect the running instance via MCP:
claude mcp add devfleet --transport http http://localhost:18801/mcp
Before first use, verify the process listening on port 18801 is the DevFleet binary you installed (see SECURITY.md on localhost MCP servers).
How It Works
User → "Build a REST API with auth and tests"
↓
plan_project(prompt) → project_id + mission DAG
↓
Show plan to user → get approval
↓
dispatch_mission(M1) → Agent 1 spawns in worktree
↓
M1 completes → auto-merge → auto-dispatch M2 (depends_on M1)
↓
M2 completes → auto-merge
↓
get_report(M2) → files_changed, what_done, errors, next_steps
↓
Report back to user
Tools
| Tool | Purpose |
|---|---|
plan_project(prompt) |
AI breaks a description into a project with chained missions |
create_project(name, path?, description?) |
Create a project manually, returns project_id |
create_mission(project_id, title, prompt, depends_on?, auto_dispatch?) |
Add a mission. depends_on is a list of mission ID strings (e.g., ["abc-123"]). Set auto_dispatch=true to auto-start when deps are met. |
dispatch_mission(mission_id, model?, max_turns?) |
Start an agent on a mission |
cancel_mission(mission_id) |
Stop a running agent |
wait_for_mission(mission_id, timeout_seconds?) |
Block until a mission completes (see note below) |
get_mission_status(mission_id) |
Check mission progress without blocking |
get_report(mission_id) |
Read structured report (files changed, tested, errors, next steps) |
get_dashboard() |
System overview: running agents, stats, recent activity |
list_projects() |
Browse all projects |
list_missions(project_id, status?) |
List missions in a project |
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.
- 2d ago First seen · 133 lines · 36 tokens per session scan A c41452287951
claude-devfleet is a skill published in the GitHub repository ufy2024/AuC (1,091 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 1,549 once invoked, about $0.0002 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 2026-09-03.
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