deploy-platform

deploy-platform is a skill for Claude Code, Codex from agno-agi/agentos-modal. It costs 82 tokens per session (1,734 once invoked), scanned A, a copy of deploy-platform, Apache-2.0.

A deployment workflow for taking a locally tested AgentOS platform and putting it on a public cloud URL. It checks the provider account, runs the deployment scripts, sets up a JWT key, and verifies the live platform.

In plain words
What is it for?
Use it to deploy, redeploy, verify, monitor, or remove an AgentOS platform running on cloud resources.
Why use it?
It removes the need to remember the production deployment steps and helps catch setup problems before or after launch. It also explains how to redeploy, view logs, and tear the platform down.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/agno-agi/agentos-modal/deploy-platform
Any agent
npx skills add agno-agi/agentos-modal --skill deploy-platform
Clone the repo
git clone --depth 1 https://github.com/agno-agi/agentos-modal

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for deploy-platform

README.md
[![agentmods](https://agentmods.dev/badge/skills/agno-agi/agentos-modal/deploy-platform.svg)](https://agentmods.dev/skills/agno-agi/agentos-modal/deploy-platform)
Your own site
<a href="https://agentmods.dev/skills/agno-agi/agentos-modal/deploy-platform"><img src="https://agentmods.dev/badge/skills/agno-agi/agentos-modal/deploy-platform.svg" alt="Measured on agentmods" height="20"></a>
Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,734 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 4d ago against content hash 2f097e6cb2e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 4d 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.

Origin

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.

.agents/skills/deploy-platform/SKILL.md · 91 lines

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-platform or 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.sh deletes everything.
  • Production env: .env.production (cp example.env .env.production if missing) with a real OPENAI_API_KEY set the setup-platform way (editor paste, never read or print). RUNTIME_ENV must not be dev there — 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.

Read the full file on GitHub · 91 lines

Changes

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.

  1. 4d ago First seen · 91 lines · 82 tokens per session scan A 2f097e6cb2e8

Subscribe to this mod's changes

deploy-platform is a skill published in the GitHub repository agno-agi/agentos-modal (2 stars, last pushed 5d 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.

Related

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…

agno-agi/agentos-docker · 82 tokens

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…

agno-agi/agentos-render · 82 tokens

modal-serverless-gpu

Run approved CPU or GPU work through OpenScience computejob on the user's configured Modal account. Use for isolated scientific scripts, dependency provisioning, durable outputs, logs, status, cancellation, and recovery. Never invoke the Modal SDK or CLI directly.

synthetic-sciences/openscience · 54 tokens

modal

Use when running Python or GPU workloads serverlessly on Modal — modal.App, inline container Images, gpu= on @app.function, Volumes for weight caching, Cron schedules, ASGI endpoints, modal run vs serve vs deploy. NOT managed prediction APIs with no container of your own (that is replicate); NOT SSH-able GPU boxes…

ericrisco/rsc-harness · 78 tokens

modal-serverless-gpu

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

davila7/claude-code-templates · 42 tokens

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…

agno-agi/agentos-docker · 87 tokens