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Agent skill

Routerbase Model Gateway

by sickn33 in sickn33/agentic-awesome-skills

Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.

MIT-0Auto-check passedAI & LLM Engineering

Install Routerbase Model Gateway

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill routerbase-model-gateway -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills routerbase-model-gateway --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/routerbase-model-gateway .claude/skills/routerbase-model-gateway && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
routerbase-model-gateway
GitHub stars
47k
Used in
1 other repo
Token cost
~1.8k tokens
SKILL.md length
710 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT-0

At a glance

Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.

  • Works in 4 steps: Classify the Workload → Configure the OpenAI-Compatible Client → Validate Model IDs and Capabilities → …
  • Tasks that involve Embeddings
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Examples, plus 5 more sections
  • Calls curl; reaches routerbase.com; needs ROUTERBASE_API_KEY

What it does

Routerbase Model Gateway is an agent skill from sickn33/agentic-awesome-skills. Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Embeddings. It works with OpenAI. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT-0.

When your agent uses it

  • Tasks that involve Embeddings

Example prompts

  • “/routerbase-model-gateway”

Requirements

  • Python 3
  • A credential in ROUTERBASE_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Classify the Workload
  2. Configure the OpenAI-Compatible Client
  3. Validate Model IDs and Capabilities
  4. Design Fallbacks Conservatively

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. 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:

    • curl

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • routerbase.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ROUTERBASE_API_KEY

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

Context cost

Routerbase Model Gateway loads about 1.8k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 710 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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 sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT-0 licence (© sickn33). 710 words, ~1,796 tokens.

Download SKILL.mdSave it as .claude/skills/routerbase-model-gateway/SKILL.md (or your agent's skills folder).
name
routerbase-model-gateway
description
Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.
category
ai-ml
risk
safe
source
community
source_repo
zenlee123/routerbase-agent-skills
source_type
community
date_added
2026-07-07
author
zenlee123
tags
routerbase, llm-routing, openai-compatible, model-gateway
tools
claude, cursor, gemini, codex, antigravity
license
MIT-0

RouterBase Model Gateway

Overview

Use routerbase when an application needs one OpenAI-compatible API surface for model routing across GPT, Claude, Gemini, image, video, audio, and embedding workloads. This skill helps agents migrate existing OpenAI SDK calls, document model-selection tradeoffs, and produce safe implementation snippets without exposing credentials.

RouterBase model availability, pricing, and provider capabilities can change, so treat examples as starting points and verify current catalog data before production recommendations.

When to Use This Skill

  • Use when migrating an OpenAI-compatible client to RouterBase by changing the base URL and model ID.
  • Use when selecting primary and fallback models for chat, reasoning, vision, media generation, audio, or embeddings.
  • Use when debugging RouterBase request setup, headers, environment variables, streaming, tool calls, JSON mode, or multimodal payloads.
  • Use when documenting an internal model-routing plan that balances cost, latency, quality, and provider redundancy.

How It Works

Step 1: Classify the Workload

Identify the modality and hard constraints before choosing a model:

  • Modality: chat, vision, image, video, audio, embeddings, or mixed.
  • Quality target: draft, production, high-stakes review, or automated background task.
  • Runtime constraints: latency budget, context length, streaming, JSON mode, tool calling, and retry tolerance.
  • Business constraints: price ceiling, provider preference, regional requirements, and fallback rules.
Step 2: Configure the OpenAI-Compatible Client

Keep the RouterBase API key server-side in an environment variable such as ROUTERBASE_API_KEY. Do not put keys in browser, mobile, or public repository code.

python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["ROUTERBASE_API_KEY"],
    base_url="https://routerbase.com/v1",
)

response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[{"role": "user", "content": "Write one sentence about model routing."}],
)

print(response.choices[0].message.content)
js
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.ROUTERBASE_API_KEY,
  baseURL: "https://routerbase.com/v1",
});

const response = await client.chat.completions.create({
  model: "google/gemini-2.5-flash",
  messages: [{ role: "user", content: "Write one sentence about model routing." }],
});

console.log(response.choices[0].message.content);
Step 3: Validate Model IDs and Capabilities

When credentials and network access are available, check the live catalog before locking in a model ID or price-sensitive recommendation.

bash
curl "https://routerbase.com/api/v1/models?task=chat" \
  -H "Authorization: Bearer $ROUTERBASE_API_KEY"

Confirm feature assumptions with a small request fixture:

  • Streaming works when stream: true is set.
  • Tool calling accepts the exact schema used by the app.
  • JSON mode returns parseable output and still passes application validation.
  • Vision or media payloads use the expected OpenAI-compatible content shape.
Step 4: Design Fallbacks Conservatively

Use explicit application-level fallbacks unless the user's RouterBase account already has a smart-routing policy configured.

js
const modelPlan = [
  "anthropic/claude-sonnet-4-6",
  "google/gemini-2.5-flash",
];

for (const model of modelPlan) {
  try {
    return await client.chat.completions.create({ model, messages });
  } catch (error) {
    if (!isRetryableRouterBaseError(error)) throw error;
  }
}

Treat transient network errors, timeouts, rate limits, and server errors as candidates for retry. Do not blindly retry authentication failures, invalid model IDs, validation errors, or policy refusals.

Examples

Migration Checklist

When converting an existing OpenAI SDK integration:

  1. Change the base URL to https://routerbase.com/v1.
  2. Read ROUTERBASE_API_KEY from server-side environment configuration.
  3. Replace the model name with a RouterBase model ID that matches the task.
  4. Preserve standard OpenAI request fields unless RouterBase documentation says otherwise.
  5. Run one minimal smoke test before shipping.
Show full SKILL.md (302 more words)Show less
Routing Plan Format

Use this table when recommending a model strategy:

Use casePrimary modelFallback modelReasonValidation
Support chatProvider/model IDProvider/model IDLow latency and acceptable qualityStreaming smoke test
Deep analysisProvider/model IDProvider/model IDStrong reasoning, higher cost acceptableEval prompt plus human review

Best Practices

  • Do keep RouterBase keys in server-side environment variables or secret managers.
  • Do verify current model availability and pricing before production decisions.
  • Do document primary and fallback model assumptions in the code or runbook.
  • Do validate structured outputs with application schemas.
  • Do not paste, log, commit, or screenshot real API keys.
  • Do not hard-code model pricing or provider availability as permanent facts.
  • Do not expose RouterBase keys in client-side JavaScript, mobile apps, or public repos.

Limitations

  • This skill does not replace RouterBase account configuration, live model catalog checks, or production observability.
  • Some model features are provider-specific and must be tested with the exact selected model.
  • High-stakes outputs still require human review and domain-specific evaluation.

Security & Safety Notes

  • Treat RouterBase credentials as production secrets.
  • Mask tokens in logs and support tickets.
  • Ask for explicit user approval before running live API calls that consume credits.
  • Use placeholders such as environment variables in examples; never invent or include realistic secret strings.

Common Pitfalls

  • Problem: The code works with one provider but fails after switching models. Solution: Re-test tool calling, JSON mode, streaming, and multimodal payloads for each selected model.

  • Problem: Fallback logic retries non-retryable errors. Solution: Retry only transient failures and fail fast on authentication, validation, and invalid model errors.

  • Problem: A model recommendation becomes stale. Solution: Re-check the RouterBase catalog and pricing page before finalizing the plan.

  • @api-analyzer - Use when the task is only to validate one API request shape.
  • @langfuse - Use when the task needs production LLM observability, tracing, and evaluation.

© sickn33, MIT-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/routerbase-model-gateway of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Routerbase Model Gateway next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Routerbase Model Gateway compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Routerbase Model Gateway this skillsickn33/agentic-awesome-skills47k1 repos~1.8kAutomated safety check: PassMIT-0
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k7 repos~2.3kAutomated safety check: PassMIT
Codebase Managementgiancarloerra/SocratiCode3.3k1 repos~1.8kAutomated safety check: PassAGPL-3.0
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k7 repos~1.7kAutomated safety check: PassMIT
Xsaimoeru-ai/airi50k1 repos~1.3kAutomated safety check: PassMIT
Embedding Strategieswshobson/agents40k10 repos~710Automated safety check: PassMIT

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Works with

Categories

Questions about Routerbase Model Gateway

What does Routerbase Model Gateway do?

Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests. Routerbase Model Gateway is an agent skill from sickn33/agentic-awesome-skills. Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.

When should I use Routerbase Model Gateway?

Routerbase Model Gateway fits situations like: tasks that involve Embeddings.

How do I install Routerbase Model Gateway in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill routerbase-model-gateway -a claude-code`. Or copy the skill folder (skills/routerbase-model-gateway in sickn33/agentic-awesome-skills) into .claude/skills/routerbase-model-gateway in your project. Claude Code loads it when a task matches its description.

How do I install Routerbase Model Gateway in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill routerbase-model-gateway -a codex`. Or copy the skill folder (skills/routerbase-model-gateway in sickn33/agentic-awesome-skills) into .agents/skills/routerbase-model-gateway in your project. Codex loads it when a task matches its description.

Can I use Routerbase Model Gateway in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill routerbase-model-gateway -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/routerbase-model-gateway, .gemini/skills/routerbase-model-gateway, .github/skills/routerbase-model-gateway and .opencode/skills/routerbase-model-gateway in your project.

What does Routerbase Model Gateway need to run?

Going by SKILL.md and its folder, Routerbase Model Gateway needs the command-line tools its instructions call (curl) and credentials named ROUTERBASE_API_KEY. Our summary lists: Python 3; A credential in ROUTERBASE_API_KEY.

Does Routerbase Model Gateway access the network?

SKILL.md names 1 domain. In commands or code: routerbase.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Routerbase Model Gateway safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Routerbase Model Gateway use?

Routerbase Model Gateway is published under the MIT-0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Routerbase Model Gateway use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Routerbase Model Gateway?

Skills that share tags, products or a category with Routerbase Model Gateway: Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Codebase Management (giancarloerra/SocratiCode, 3.3k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Xsai (moeru-ai/airi, 50k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Routerbase Model Gateway?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.