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/agno-agi/agentos-render/deploy-platformnpx skills add agno-agi/agentos-render --skill deploy-platformgit clone --depth 1 https://github.com/agno-agi/agentos-renderWhat 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 | $0.00082 | $0.01734 |
| Opus 5 | $0.00041 | $0.00867 |
| Sonnet 5 | $0.00016 | $0.00347 |
| Haiku 4.5 | $0.00008 | $0.00173 |
Grade A, and why
deploy-platform 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.
This is a copy
100% identical to deploy-platform — 0 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy the Platform
Coding-agent workflow: run as
/deploy-platformor by describing the task.
Take the locally-proven platform to a live public URL. This creates real, billed cloud resources — say so before creating anything, and name the teardown script in the same breath.
Be self-driving: run every script and check yourself. Stop only for a provider login, a browser-only step, or a key only the user can mint — and tell them to run interactive commands in a separate terminal (CLI logins need a TTY and a browser). Never print secret values; the two exceptions are the JWT verification key (public) and the MCP_CONNECT_SECRET the up script prints itself.
Narrate: open with this map plus the cost sentence, then a line per step. On a redeploy (Step 3 finds the platform live) the map is three beats — push, prove, hand back — and the cost sentence is already spent.
Kicking off /deploy-platform. Here's the map:
1. Read the deploy layer — scripts + README, pick the mode
2. Preflight — provider CLI + login, cost and exit, production env
3. Deploy — the up script (compute + Postgres + public domain)
4. JWT key — connect os.agno.com Live, land the public key, sync it
5. Prove it live — logs, /docs 200, /mcp 401 challenge, UI Connect
6. Hand over — redeploy, logs, teardown, chat + coding-agent connect
This creates real, billed resources on your account. The exit is one
command away — the down script deletes everything (asks to confirm; --yes skips).
1. Read the deploy layer
Read AGENTS.md, the README's production section, and scripts/<provider>/ — never invent a step. Pick the mode by who provisions the target: Conduct (the up script provisions compute and URL on a managed provider — the main path), Conduct over owned infra (same scripts onto the user's own cluster; add Step 7), or Manual-guide (no deploy scripts; walk the README's deploy section with Steps 4, 5, and 7).
2. Preflight
- CLI + account: the provider CLI is installed and authed (a
whoami-style probe). Not logged in → hand over the login command for a separate terminal, re-probe when they say ready. - Cost + exit: one sentence — billed resources,
down.shdeletes everything. - Production env:
.env.production(cp example.env .env.productionif missing) with a realOPENAI_API_KEYset the setup-platform way (editor paste, never read or print).RUNTIME_ENVmust not bedevthere — it syncs to the cloud and disables auth. - Unattended-run inputs: for each provisioning call the up script makes, does it pin the account scope (workspace, org, project, region)? If the account has more than one and nothing pins it, the CLI opens a picker that fails or hangs — stop before creating anything and hand the user the pinning flag/env var or the one interactive init/link command. Never let it resolve by guess.
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 · 91 lines · 82 tokens per session scan A 2f097e6cb2e8
deploy-platform is a skill published in the GitHub repository agno-agi/agentos-render (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 82 tokens to every session and 1,734 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to deploy-platform, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
deploy-platform
Deploy this AgentOS to production with this template's deploy scripts — preflight the provider CLI and account, run the up.sh script, complete the JWT key step, verify the live platform on its public URL, then hand over the redeploy/logs/teardown instructions. Use this skill when the user asks to deploy, ship to…
setup-platform
Set up this AgentOS from a fresh clone — confirm Docker, configure .env, boot the containers, prove the MCP endpoint live, connect the AgentOS UI, then build the user's first agent. Use when the user asks to set up the platform, get started, or bring this repo up on a new machine.
deploy-platform
Deploy this AgentOS to production with this template's deploy scripts — preflight the provider CLI and account, run the up.sh script, complete the JWT key step, verify the live platform on its public URL, then hand over the redeploy/logs/teardown instructions. Use this skill when the user asks to deploy, ship to…
setup-platform
Set up this AgentOS from a fresh clone — confirm Docker, configure .env, boot the containers, prove the MCP endpoint live, connect the AgentOS UI, then build the user's first agent. Use when the user asks to set up the platform, get started, or bring this repo up on a new machine.
improve-agent
Autonomous hardening loop for an existing agent — derive probes from the agent's INSTRUCTIONS and from its real usage recorded in the database, run them against the live container, judge responses, edit the agent file, and re-probe until it reliably does what its instructions say. No user input needed. Use to harden…
eval-and-improve
Run the eval suite (python -m evals), diagnose every failure, fix what's in scope, and loop until all cases pass. Use when evals are failing — including overnight run-evals schedule failures — or when the user wants to run, diagnose, or repair the eval suite. To author new coverage, use create-evals instead.