- name
- safe-long-run-mode-gpt54-claude
- description
- Operate long-running AI tasks safely across GPT-5.4 and Claude by using model selection rules, phased execution, checkpoints, resumable workflows, API throttling discipline, and subagent isolation. Use when a task may run for a while, touch multiple files/systems, involve external APIs, browser automation, Azure, Orgo, or multiple subagents, or when the user asks about long autonomous runs, rate limits, reliability, or safe operating mode.
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:
- gather / inspect
- plan / write brief
- execute / edit / build
- validate
- 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:
- summarize completed phases
- point to saved artifacts
- identify exact next step
- resume from checkpoint rather than restarting
References
- Read
references/checklist.mdfor a reusable pre-flight checklist and model routing matrix.