safe-long-run-mode-gpt54-claude

# Safe Long-Run Mode (GPT-5.4 + Claude) Use this skill for tasks that may run long, span multiple systems, or risk losing progress if interrupted. ## Core rule Do not run long tasks as one monolithic attempt. Split into phases, write checkpoints, and keep the work resumable. ## Model selection Use **GPT-5.4** for: - coding - docs - research - file-heavy transformations - multi-agent delegated work - repetitive build tasks - long internal work where cost and throughput matter Use **Claude** for: - strategic judgment - sensitive decisions - nuanced synthesis - client-facing polish - brand voice refinement - high-trust orchestration Default to **GPT-5.4 first**. Escalate to Claude only when the task actually benefits from higher-quality judgment or tone. ## Operating procedure ### 1. Scope before acting Before starting, decide: - what the final deliverable is - which systems/tools will be touched - what can fail or throttle - what must be saved after each phase ### 2. Break work into phases Use phases such as: 1. gather / inspect 2. plan / write brief 3. execute / edit / build 4. validate 5. deploy or report At the end of each phase, write artifacts to disk. ### 3. Always checkpoint For long tasks, save progress in files: - draft outputs - notes - reports - partial results - tracker entries - checkpoint summaries Prefer a resumable workspace state over a perfect one-shot run. ### 4. Isolate long work Use subagents when: - the task will take more than a few tool calls - multiple files/systems are involved - external APIs are involved - failure should not pollute the main session - specialized work can be delegated cleanly ### 5. Throttle external systems When interacting with Azure, Graph, Orgo, messaging providers, registries, websites, or any external API: - batch reads when possible - avoid tight polling loops - serialize risky writes - respect retry/backoff - avoid one-item burst loops when a bulk operation is possible ### 6. Prefer resumability over perfection The goal is not "never fail." The goal is: if interrupted, resume with minimal loss. ## System-specific guidance ### Azure / cloud control planes - validate auth first - create foundational resources first - verify after each layer - log resource names/IDs - do not chain long destructive commands blindly ### Browser / Orgo / GUI automation - use explicit goals and stop conditions - capture screenshots at checkpoints - bound retry counts - save artifacts locally - prefer API/CLI over GUI when equivalent exists ### Coding / documentation work - create a brief/spec first for complex tasks - write files in chunks - validate after each major change - leave notes for resume if work is unfinished ## What to tell the user When relevant, explain that safe long-run mode means: - cheapest adequate model - phased execution - saved checkpoints - subagent isolation - controlled API usage - resumable progress ## Failure handling If a long task is interrupted: 1. summarize completed phases 2. point to saved artifacts 3. identify exact next step 4. resume from checkpoint rather than restarting ## References - Read `references/checklist.md` for a reusable pre-flight checklist and model routing matrix.