Sends prompts to the OpenAI API with automatic model selection and token logging.
npx skills add https://github.com/tinner-deinno/innova-skills-lib --skill model-gpt
Please help me install this Agent Skill. Skill: model-GPT Source: https://github.com/tinner-deinno/innova-skills-lib/tree/main/core/model-GPT Command: npx skills add https://github.com/tinner-deinno/innova-skills-lib --skill model-gpt
The model-GPT skill eliminates the time spent manually picking and calling the correct OpenAI model by routing your task to an appropriate GPT/o1/o3 variant and returning the response with consistent handling.
Run /model-GPT Explain how multi-agent systems work in Thai to get a best-fit OpenAI GPT response using the default model.
High-intent search queries and answers about installing and using this skill.
Automatic model routing sends your prompt to an appropriate GPT or reasoning variant by analyzing task keywords like long-context or deep reasoning, returning completions without manual selection.
To generate task-specific completions, configure your OPENAI_API_KEY in the ~/Jit/.env file, then execute your prompt command to send requests directly to the OpenAI API for processing.
Yes, you can bypass auto-routing logic by passing the --model flag with your prompt command to explicitly select a specific OpenAI GPT or reasoning model for the task.
Token usage logging happens automatically during API execution, recording token counts and usage data to ~/Jit/ψ/telemetry/token_log.jsonl to enable tracking and auditing of OpenAI API consumption.
Yes, the integration supports long-context and deep reasoning tasks by routing prompts to appropriate OpenAI reasoning models, alongside handling general Q&A, summarization, formatting, and translation.
Auto-routing relies on task keywords to select models, which may not always match complex or ambiguous prompt requirements; use --model for explicit selection when precise control over the OpenAI variant is needed.
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