Render Networking logo

Render Networking

Organization
render-oss
render-networking

Connects Render services over the private network—internal DNS, service discovery, and cross-service communication. Use when the user needs to wire services together, resolve internal hostnames, troubleshoot connectivity between services, configure environment isolation, or understand which services can reach each other.

Overview

Publisherrender-oss
Repositoryskills
Skill namerender-networking
Stars
90
Forks
21
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by render-oss on GitHub. Read the source before you install it.

Installation

Install the Render Networking AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/render-oss/skills/tree/main/skills/render-networking
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/render-oss/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/render-networking .claude/skills/render-networking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Networking in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Render Networking on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Render Networking is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Render private networking

Render’s private network lets services talk to each other without exposing traffic on the public internet. Use this skill when users need internal connectivity, discovery across scaled instances, or correct URL/port behavior for Blueprints and the Dashboard.

When to Use This Skill

  • Designing or debugging service-to-service traffic on Render
  • Questions about internal hostnames, internal URLs, or Connect > Internal in the Dashboard
  • Service discovery across multiple instances (custom load balancing, mesh-style setups)
  • Port limits, reserved ports, or multi-port web services (public vs private)
  • Free-tier web services and who can send vs receive private traffic
  • Environment isolation (with a Pro workspace or higher) or AWS PrivateLink for private egress/ingress patterns

Before designing, configuring, or troubleshooting private connectivity, read references/private-networking.md. For architecture examples and Blueprint patterns, see references/communication-patterns.md.

Private Connection Essentials

  • If the service types or traffic direction are unclear, establish which service initiates the connection and which service receives it before proposing an address.
  • Private-network peers must be in the same workspace and region. Use the destination's address from Connect > Internal in the Dashboard.
  • Construct a complete URL when the client expects one, such as http://[internal-hostname]:[port]/path; a bare hostname does not supply the protocol.
  • Web services and private services can receive private traffic. Background workers, cron jobs, and workflow runs can initiate outbound private connections but have no internal hostname and cannot receive them.
  • In a gateway pattern, a public web service calls a private service over the private network; the private service does not need a public endpoint.

Service Discovery

Use a service's normal internal hostname for ordinary service-to-service traffic. When an application specifically needs every active instance—for custom load balancing, per-instance metrics, or similar logic—use the service's discovery hostname, conventionally [internal-hostname]-discovery, which resolves to all active instance IPs. Each web or private service receives its own discovery hostname in RENDER_DISCOVERY_SERVICE. Do not persist the resolved IPs because they can change between deploys.

Common Patterns

Short summaries; full diagrams and Blueprint notes live in references/communication-patterns.md.

  1. Web gateway + private backends — Public Web Service terminates HTTP; internal calls use private hostnames and ports to Private Services or internal URLs.
  2. Worker to database — Background Worker (no internal hostname) connects outbound to Postgres or Key Value internal URLs.
  3. Microservices — Private Services (and eligible Web Services) call each other by internal hostname:port on the private network.

References

DocumentPurpose
references/private-networking.mdCurrent private-network capabilities, addressing, discovery, ports, isolation, and troubleshooting
references/communication-patterns.mdGateway, worker→DB, mesh, URL construction, and Blueprint fromService patterns

Related Skills

  • render-web-services — Public web services, PORT, and HTTP behavior
  • render-private-services — Private Service–specific setup and scaling
  • render-blueprints — render.yaml, fromService, and multi-service wiring

Current documentation retrieval

Whenever this skill directs you to consult current Render documentation:

  1. Retrieve the linked Markdown document directly with an available URL-fetching tool or HTTP client, such as curl. Do not substitute web-search summaries for the document.
  2. Confirm that retrieval succeeded and returned the expected document, then read its contents. Saving a file or printing its path is not sufficient.
  3. If the request fails or your tool cannot read the Markdown response, open and read the linked HTML version instead.
  4. If neither version can be retrieved, disclose that the current reference is unavailable and follow any topic-specific fallback in the skill. Use bundled guidance only for stable constraints, and do not guess at changeable platform details.

When a task requires multiple references, apply this workflow to each one and distinguish the documents you verified from those that remain unavailable.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Render Networking AI skill do?

Connects Render services over the private network—internal DNS, service discovery, and cross-service communication. Use when the user needs to wire services together, resolve internal hostnames, troubleshoot connectivity between services, configure environment isolation, or understand which services can reach each other.

Why use Render Networking on TypingMind?

Because you install it once and use it with any model. Render Networking is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Render Networking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/render-oss/skills/tree/main/skills/render-networking. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Render Networking?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Render Networking?

As many as you like. As long as a model supports skills, you can use Render Networking with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Render Networking AI skill free?

Yes. It is published on GitHub by render-oss under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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