gpt-api-gateway_skill

This skill lets you access multiple GPT models without an OpenAI account, enabling zero-markup, diverse options, and failover.
  • Python

2.5k

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill gpt-api-gateway

  • _meta.json285 B
  • SKILL.md2.0 KB

Overview

This skill provides an OpenAI-compatible gateway to a full range of GPT and reasoning models without requiring an OpenAI account. It exposes GPT-5, GPT-5.1, GPT-5-mini, GPT-5-nano, o1, o3-mini, o4-mini, GPT-4o variants, and more through a familiar API interface with no markup on pricing. The gateway supports high-volume use, failover routing, and simple command-style invocation for quick integration.

How this skill works

The gateway proxies requests to hosted GPT and reasoning models and returns OpenAI-compatible responses so existing code and tools work unchanged. Requests are routed to the best available model or to fallback providers (Claude/Gemini) if the primary service is unavailable. Pricing mirrors provider rates, and the gateway includes endpoints for fast, cost-optimized, and multimodal models.

When to use it

  • Run GPT models without provisioning an OpenAI account or keys.
  • Switch between high-accuracy and low-cost models for different workloads.
  • Integrate GPT-4o multimodal capabilities into apps without API changes.
  • Handle bulk processing with nano/mini tiers to reduce costs.
  • Enable automatic failover to alternate providers when reliability matters.

Best practices

  • Choose model families by trade-off: GPT-5 for quality, mini/nano for bulk cost savings.
  • Profile latency and cost per million tokens before production scale-up.
  • Implement model-specific prompts and temperature tuning for consistent results.
  • Use failover only for non-sensitive workloads or test fallback outputs before relying on them.
  • Monitor usage and set token quotas to control unexpected spend.

Example use cases

  • Creative content pipelines: use GPT-5 for high-quality drafts and GPT-5-nano for bulk rewrites.
  • Reasoning and analytics: route complex problem solving to o1/o4-mini models.
  • Multimodal apps: accept images or attachments with GPT-4o for richer outputs.
  • Cost-sensitive batch jobs: run classification or parsing with GPT-5-nano at scale.
  • Disaster recovery: automatically failover to alternate providers when primary endpoints fail.

FAQ

No. The gateway is designed to work without an OpenAI account or keys; it provides an OpenAI-compatible API layer.

How do I choose between models?

Select models by the accuracy/latency/cost trade-off: flagship GPT-5 for quality, mini/nano for cost, and o-series for reasoning tasks.

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