Deploy AI Agent

What it does

When your agent uses it

• Tasks that involve Cryptography
• Tasks that involve Building AI agents
• Tasks that involve Deployment

Example prompts

• “/deploy-ai-agent”

Requirements

• Python 3
• Node.js

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Understand — Ask what agent framework they're using and what it needs (model provider, API keys, GPU, dependencies)
2. 2Check resources — Use system_health to verify RAM, disk, and CPU are sufficient. Check for GPU with shell_exec running nvidia-smi or ls…
3. 3Set up environment — Create a Python venv, install Node.js deps, or verify Go binary. Write API keys to the secrets directory.
4. 4Deploy — Use app_deploy with appropriate resource limits, environment variables pointing to secrets, and a health-check-friendly port
5. 5Verify — Check app_logs for successful startup. Use system_discover to confirm the agent's port is listening.
6. 6Monitor — Set up a watcher via watcher_add to auto-restart on failure
7. 7Remember — Use memory_store to save deployment details for future reference

What it can do on your machine

Read from SKILL.md and the folder at commit b8e418f. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • python3
  • node

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deploy AI Agent loads about 1.1k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 362 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~28

When it runs · the whole SKILL.md, loaded when a task matches

~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from bolivian-peru/os-moda at commit b8e418f, republished under its Apache-2.0 licence (© bolivian-peru). 362 words, ~1,132 tokens.

name

deploy-ai-agent

description

Deploy and manage AI agent workloads with GPU checks, API key management, and health monitoring

activation

auto

tools

app_deploy, app_list, app_logs, app_stop, app_restart, app_remove, system_discover, system_health, system_query, shell_exec, file_write, file_read…

app_deploy({
  name: "my-agent",
  command: "/var/lib/osmoda/apps/my-agent/venv/bin/uvicorn",
  args: ["app:app", "--host", "0.0.0.0", "--port", "8000"],
  working_dir: "/var/lib/osmoda/apps/my-agent",
  env: {
    ANTHROPIC_API_KEY_FILE: "/var/lib/osmoda/secrets/anthropic-key",
    OPENAI_API_KEY_FILE: "/var/lib/osmoda/secrets/openai-key"
  },
  port: 8000,
  memory_max: "1G",
  cpu_quota: "200%"
})

app_deploy({
  name: "crew-agent",
  command: "/var/lib/osmoda/apps/crew-agent/venv/bin/python",
  args: ["-m", "crew_agent.main"],
  working_dir: "/var/lib/osmoda/apps/crew-agent",
  env: {
    ANTHROPIC_API_KEY_FILE: "/var/lib/osmoda/secrets/anthropic-key"
  },
  port: 8001,
  memory_max: "2G"
})

app_deploy({
  name: "node-agent",
  command: "/usr/bin/node",
  args: ["index.js"],
  working_dir: "/home/user/agent",
  env: {
    NODE_ENV: "production",
    PORT: "3000",
    API_KEY_FILE: "/var/lib/osmoda/secrets/agent-api-key"
  },
  port: 3000,
  memory_max: "512M"
})

watcher_add({
  name: "my-agent-health",
  check: {
    type: "http_get",
    url: "http://127.0.0.1:8000/health",
    expected_status: 200
  },
  interval_secs: 30,
  actions: ["restart", "notify"]
})

watcher_add({
  name: "my-agent-alive",
  check: {
    type: "systemd_unit",
    unit: "osmoda-app-my-agent.service"
  },
  interval_secs: 60,
  actions: ["restart", "notify"]
})

© bolivian-peru, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/deploy-ai-agent of bolivian-peru/os-moda.

Open the folder on GitHubat commit b8e418f