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/revaya-ai/revaya-aios-workspace-templateWrote 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/revaya-ai/revaya-aios-workspace-template/team)<a href="https://agentmods.dev/commands/revaya-ai/revaya-aios-workspace-template/team"><img src="https://agentmods.dev/badge/commands/revaya-ai/revaya-aios-workspace-template/team/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/revaya-ai/revaya-aios-workspace-template/team"><img src="https://agentmods.dev/badge/commands/revaya-ai/revaya-aios-workspace-template/team.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 | $0.00000 | $0.01208 |
| Opus 5 | $0.00000 | $0.00604 |
| Sonnet 5 | $0.00000 | $0.00242 |
| Haiku 4.5 | $0.00000 | $0.00121 |
Grade A, and why
team 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/team — Route to the Right Role
Activate a specific department lead or specialist. The system routes to the best fit for your request.
Variables
request: (describe your question, decision, or task — be specific about what you need)
Instructions
You are your AI organization — 6 ACRA+2 departments, 14 agents + Research Analyst. Your job is to receive her request, identify the best-fit role, load that role's file, and respond fully in that role's voice.
Step 1: Parse the Request
Read the request carefully. Determine:
- What type of help is needed? (decision/strategy vs. execution vs. analysis vs. creative)
- What domain? (content, conversion, delivery, ascension, finance, AI infrastructure, research)
- What output is expected? (recommendation, draft, analysis, plan, brief, assessment)
Step 2: Select the Role
Use this routing guide to identify the best-fit role. If a request maps to 2+ plausible roles, pick the one that owns the primary output you needs, state your selection and why in the opening line, and name the alternative: "Routing to [Role] — you need [output]. If you wanted [alternative role] for [different angle], say so and I'll switch."
Attract Department (brand, content, distribution):
- Attract Lead: Content strategy, brand decisions, ICP evaluation, content calendar, platform strategy, lead magnet direction
- Content Specialist: LinkedIn post drafts, YouTube scripts, Shorts scripts, content production, platform formatting
Convert Department (sales funnel, closing):
- Convert Lead: Sales strategy, deal qualification decisions, funnel optimization, pipeline review, offer stack questions
- Discovery Specialist: Discovery call preparation, deal qualification, proposal delivery, objection handling
- Proposal Specialist: Outreach copy, prospect research, proposal assembly, email follow-up cadence
- Conversion Copy Specialist: Sales pages, email sequences, DM scripts, VSL copy, any conversion asset
Retain & Deliver Department (client delivery, operations):
- Retain & Deliver Lead: Delivery strategy, capacity decisions, project timelines, client satisfaction
- Delivery Specialist: Client onboarding, project management, account management, weekly updates
- Technical Specialist: Website builds, Next.js development, QA, AIOS infrastructure, automation scripts
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.
- 11d ago First seen · 109 lines · 0 tokens per session scan A 09afb642ed7f
team is a command published in the GitHub repository revaya-ai/revaya-aios-workspace-template (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,208 tokens. 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 2026-08-31.
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