safe-long-run-mode-gpt54-claude

What This Skill Does

The Safe Long-Run Mode (GPT-5.4 + Claude) skill is designed for high-stakes, multi-step, or time-intensive AI workflows. It acts as a framework for execution, ensuring that complex tasks are treated as manageable, resumable sequences rather than fragile monolithic operations. By leveraging a hybrid model approach—utilizing GPT-5.4 for cost-effective heavy lifting and Claude for nuanced, strategic orchestration—this skill provides a robust architecture for AI reliability.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/bwiley1989/safe-long-run-mode-gpt54-claude

Use Cases

This skill is ideal for:

• Large-scale refactoring of legacy codebases spanning multiple repositories.
• Automated research projects involving multiple external API lookups and data aggregation.
• Orchestrating complex deployments across cloud providers like Azure where verification steps are required between layers.
• Managing long-duration browser automation tasks, such as systematic data gathering from Orgo or web portals.
• Any task where total execution time exceeds typical interaction windows, requiring robust checkpointing to ensure work is never lost.

Example Prompts

1. "I need to migrate our legacy module documentation across 50 files. Please use the safe long-run mode to break this into phases, checkpointing each file, and use GPT-5.4 for the bulk of the drafting while using Claude for the final policy alignment check."
2. "We have a massive data gathering task from the internal web portal. Can you set up a resumable workflow that periodically saves our progress to local JSON files so that if the network drops, we don't have to restart from scratch?"
3. "Please automate our deployment pipeline check. I need you to validate our Azure resources step-by-step, logging every ID and saving the state after each successful sub-module build."

Tips & Limitations

• Always Checkpoint: The effectiveness of this skill relies on the user and the agent consistently writing artifacts to disk. If you omit the checkpointing phase, you lose the safety benefits.
• Model Selection: Default to GPT-5.4 for standard coding and logic. Only invoke Claude for high-level decision-making to maintain cost efficiency.
• Subagent Isolation: Use this to keep your main workspace clean. If a subagent task fails, it should not affect the validity of your entire project directory.
• Rate Limit Awareness: Always respect the API throttling discipline. Do not attempt to blast thousands of requests; use batching and serialized writes to stay within provider limits.