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 skills add boshi-xixixi/TraeSkill --skill ai-team-orchestrationgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote 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/boshi-xixixi/traeskill/ai-team-orchestration)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/ai-team-orchestration"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/ai-team-orchestration/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/skills/boshi-xixixi/traeskill/ai-team-orchestration"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/ai-team-orchestration.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 | $0.00058 | $0.01421 |
| Opus 5 | $0.00029 | $0.00711 |
| Sonnet 5 | $0.00012 | $0.00284 |
| Haiku 4.5 | $0.00006 | $0.00142 |
Grade A, and why
ai-team-orchestration 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 12d 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
1 near-identical copy found in the catalogue:
- ai-team-orchestration — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Team Orchestration
When to Use
- Starting a new project that needs planning, development, testing, and deployment
- Setting up parallel AI agent teams (dev, QA, DevOps)
- Writing brainstorm prompts that produce real debate (not generic output)
- Creating sprint plans with cross-chat context survival
- Recovering from context overflow mid-sprint
Team Roles
| Agent | Name | Role | Focus |
|---|---|---|---|
| Producer | Remy | Sprint planning, coordination, merging PRs | Scope control, handoffs, issue triage |
| Product Designer | Kira | UX, mechanics, user experience | Fun factor, user flows, feature design |
| Visual/Art Director | Milo | CSS, animations, visual identity | Design system, polish, accessibility |
| Frontend Engineer | Nova | UI framework, state management, components | React/Vue/Svelte, client-side logic |
| Backend Engineer | Sage | API, database, auth, security | Server-side logic, infrastructure |
| DevOps Engineer | Dash | CI/CD, cloud deployment, pipelines | GitHub Actions, Azure/AWS/GCP |
| QA Engineer | Ivy | E2E tests, automation, playtesting | Playwright/Cypress, bug filing, sign-off |
Customize names and roles for your project. Not every project needs all roles.
Chat Architecture
The human (CEO) is the message bus between parallel chats:
┌────────────────────────────────────────┐
│ @ai-team-producer — Plans, merges │
│ NEVER writes code │
└────────────────┬───────────────────────┘
│ Human carries messages
┌──────────┼──────────┐
▼ ▼ ▼
┌──────────┐ ┌────────┐ ┌────────┐
│@ai-team │ │@ai-team│ │DevOps │
│-dev │ │-qa │ │(on │
│ │ │ │ │demand) │
│ Nova │ │ Ivy │ │ │
│ Sage │ │ │ │ │
│ Milo │ │ │ │ │
│ │ │feature/│ │feature/│
│ feature/ │ │qa-N │ │devops-N│
│ sprint-N │ └────────┘ └────────┘
└──────────┘
Each team works in a separate VS Code window with its own clone:
git clone <repo> project-dev # Dev team
git clone <repo> project-qa # QA
git clone <repo> project-devops # DevOps (only when needed)
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.
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.
- 12d ago First seen · 149 lines · 58 tokens per session scan A be73d0a778f7
ai-team-orchestration is a skill published in the GitHub repository boshi-xixixi/TraeSkill (263 stars, last pushed 4mo ago), licensed MIT. It adds 58 tokens to every session and 1,421 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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