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.
git clone --depth 1 https://github.com/multiplex-ai/muggle-ai-teamsWrote 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/commands/multiplex-ai/muggle-ai-teams/devfleet)<a href="https://agentmods.dev/commands/multiplex-ai/muggle-ai-teams/devfleet"><img src="https://agentmods.dev/badge/commands/multiplex-ai/muggle-ai-teams/devfleet/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.
<a href="https://agentmods.dev/commands/multiplex-ai/muggle-ai-teams/devfleet"><img src="https://agentmods.dev/badge/commands/multiplex-ai/muggle-ai-teams/devfleet.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00033 | $0.00865 |
| Opus 5.5 | $0.00013 | $0.00346 |
| Sonnet 5.5 | $0.00007 | $0.00173 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
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 1mo 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.
This is a copy
94% identical to devfleet — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DevFleet — Multi-Agent Orchestration
Orchestrate parallel Claude Code agents via Claude DevFleet. Each agent runs in an isolated git worktree with full tooling.
Requires the DevFleet MCP server: claude mcp add devfleet --transport http http://localhost:18801/mcp
Flow
User describes project
→ plan_project(prompt) → mission DAG with dependencies
→ Show plan, get approval
→ dispatch_mission(M1) → Agent spawns in worktree
→ M1 completes → auto-merge → M2 auto-dispatches (depends_on M1)
→ M2 completes → auto-merge
→ get_report(M2) → files_changed, what_done, errors, next_steps
→ Report summary to user
Workflow
- Plan the project from the user's description:
mcp__devfleet__plan_project(prompt="<user's description>")
This returns a project with chained missions. Show the user:
- Project name and ID
- Each mission: title, type, dependencies
- The dependency DAG (which missions block which)
-
Wait for user approval before dispatching. Show the plan clearly.
-
Dispatch the first mission (the one with empty
depends_on):
mcp__devfleet__dispatch_mission(mission_id="<first_mission_id>")
The remaining missions auto-dispatch as their dependencies complete (because plan_project creates them with auto_dispatch=true). When manually creating missions with create_mission, you must explicitly set auto_dispatch=true for this behavior.
- Monitor progress — check what's running:
mcp__devfleet__get_dashboard()
Or check a specific mission:
mcp__devfleet__get_mission_status(mission_id="<id>")
Prefer polling with get_mission_status over wait_for_mission for long-running missions, so the user sees progress updates.
- Read the report for each completed mission:
mcp__devfleet__get_report(mission_id="<mission_id>")
Call this for every mission that reached a terminal state. Reports contain: files_changed, what_done, what_open, what_tested, what_untested, next_steps, errors_encountered.
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.
- 1mo ago First seen · 93 lines · 33 tokens per session scan A 409d9642905a
devfleet is a command published in the GitHub repository multiplex-ai/muggle-ai-teams (2 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 865 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to devfleet, differing in 7 lines, and is treated as a copy.
Other commands, from other repositories
check-web-perf
Diagnostic command to check web performance toolkit setup and dependencies.
diagnose-runtime
Quickly diagnose runtime performance issues in web applications including freezes, hangs, memory leaks, and slow performance.
map-class-usage
Build comprehensive usage map for a class showing all methods and fields with their usages.
scan-codebase
Comprehensive codebase scan and structure mapping.
analyze-file
Deep analysis of a specific file using code-analyst sub-agent.
paul:help
Show available PAUL commands and usage guide.