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 xyva-yuangui/XyvaClaw --skill agent-team-orchestrationgit clone --depth 1 https://github.com/xyva-yuangui/XyvaClawWrote 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/xyva-yuangui/xyvaclaw/agent-team-orchestration)<a href="https://agentmods.dev/skills/xyva-yuangui/xyvaclaw/agent-team-orchestration"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/agent-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/xyva-yuangui/xyvaclaw/agent-team-orchestration"><img src="https://agentmods.dev/badge/skills/xyva-yuangui/xyvaclaw/agent-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 | $0.00102 | $0.01330 |
| Opus 5 | $0.00051 | $0.00665 |
| Sonnet 5 | $0.00020 | $0.00266 |
| Haiku 4.5 | $0.00010 | $0.00133 |
Grade A, and why
agent-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.
This is a copy
95% identical to agent-team-orchestration — 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Team Orchestration
Production playbook for running multi-agent teams with clear roles, structured task flow, and quality gates.
Quick Start: Minimal 2-Agent Team
A builder and a reviewer. The simplest useful team.
1. Define Roles
Orchestrator (you) — Route tasks, track state, report results
Builder agent — Execute work, produce artifacts
2. Spawn a Task
1. Create task record (file, DB, or task board)
2. Spawn builder with:
- Task ID and description
- Output path for artifacts
- Handoff instructions (what to produce, where to put it)
3. On completion: review artifacts, mark done, report
3. Add a Reviewer
Builder produces artifact → Reviewer checks it → Orchestrator ships or returns
That's the core loop. Everything below scales this pattern.
Core Concepts
Roles
Every agent has one primary role. Overlap causes confusion.
| Role | Purpose | Model guidance |
|---|---|---|
| Orchestrator | Route work, track state, make priority calls | High-reasoning model (handles judgment) |
| Builder | Produce artifacts — code, docs, configs | Can use cost-effective models for mechanical work |
| Reviewer | Verify quality, push back on gaps | High-reasoning model (catches what builders miss) |
| Ops | Cron jobs, standups, health checks, dispatching | Cheapest model that's reliable |
→ Read references/team-setup.md when defining a new team or adding agents.
Task States
Every task moves through a defined lifecycle:
Inbox → Assigned → In Progress → Review → Done | Failed
Rules:
- Orchestrator owns state transitions — don't rely on agents to update their own status
- Every transition gets a comment (who, what, why)
- Failed is a valid end state — capture why and move on
→ Read references/task-lifecycle.md when designing task flows or debugging stuck tasks.
Handoffs
When work passes between agents, the handoff message includes:
What ships with it
13 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.
- _meta.json 634 B
- .clawhub/origin.json 156 B
- examples/README.md 726 B
- references/communication.md 3.5 KB
- references/patterns.md 4.3 KB
- references/task-lifecycle.md 3.5 KB
- references/team-setup.md 3.6 KB
- scripts/check.py 407 B runs code
- scripts/README.md 67 B
- team_creator.py 7.9 KB runs code
- templates/content-team.json 2.6 KB
- templates/dev-team.json 2.5 KB
- templates/research-team.json 2.3 KB
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 · 136 lines · 102 tokens per session scan A 500a52db5a52
agent-team-orchestration is a skill published in the GitHub repository xyva-yuangui/XyvaClaw (21 stars, last pushed 1mo ago), licensed MIT. It adds 102 tokens to every session and 1,330 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to agent-team-orchestration, differing in 7 lines, and is treated as a copy.
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