| title | Run long-running AI coding agents with Codex and Claude Code |
|---|---|
| description | Keep Codex and Claude Code work moving across sessions with LoopX. Set up durable goals, resume from evidence, coordinate review, and stop at human approval gates. |
Use LoopX when a coding task spans sessions, waits for review or CI, or needs handoff between agents. Your coding agent still edits and tests the code. LoopX preserves the goal, task ownership, decisions, evidence and next action outside the conversation so another authorized turn can continue the work.
For a small task that fits in one session, start with the agent you already use. A host's native Goal can also be sufficient when continuation stays in one host. The session, Codex Goal and LoopX comparison explains when project-level state earns its additional setup.
Run the no-clone installer, then open the project you want your agent to work on:
curl -fsSL https://loopx-project.github.io/loopx/install.sh | bash
export PATH="$HOME/.local/bin:$PATH"
cd /path/to/your-project
loopx doctor
loopx connect
loopx statusconnect should reuse an existing connection. If state is missing, follow the
guided first-goal path; do not
replace an existing goal just to restart a session. Keep runtime state out of
version control as described in the installation guide.
In Codex App, use the installed loopx skill through $loopx or /skills.
A useful first task has a bounded result and a clear stopping rule:
$loopx Fix the failing integration test, explain the cause, and prepare a
reviewable PR. Preserve the existing project goal and record test evidence.
Wait for my approval before merging.
For Codex CLI, start from the project root and use the generated bootstrap message:
loopx codex-cli-bootstrap-message --project .Follow the returned instructions in the actual Codex session. App automation, visible CLI continuation and isolated headless execution have different host contracts; they are not interchangeable. The driver selection table and Codex App chapter explain activation. Installing LoopX by itself does not keep a closed or unavailable host running.
The installer registers lightweight Claude Code skills. Use /loopx with the
same concrete result and approval boundary. Check loopx doctor if the command
is not available, and follow the skill registration guide.
If one agent implements while another reviews, retain separate ownership and return the review evidence to the shared task. The Claude implementation / Codex review example shows the roles and acceptance boundary. Switching the executor does not grant it another agent's identity or the user's merge authority.
For a DSH Web session, the native LoopX plugin provides bootstrap, workflow skills, a session-bound Driver and GoalBar. Follow its install instructions and version compatibility notes: the published prebuilt artifact and the latest source checkout can target different DSH versions. Installing the plugin alone does not activate continued work.
Use the DeepSeek Harness SDK connector when an outer supervisor needs bounded headless turns instead. It is a different integration from the native Web plugin.
Open the same project and read loopx status before issuing another task.
Ask the agent to summarize the active goal, current owner, pending decision,
last accepted evidence and next permitted action. Explicitly select the prior
agent identity if you intend to resume that lane; sharing a goal is not enough
to infer identity takeover.
A compact restart instruction is:
Read this project's existing LoopX state. Report the current goal, pending
user gate, last accepted result, and next permitted task. Reuse the existing
goal. Ask me to select the prior agent identity if a takeover is needed.
Continue only the authorized task and verify the result before writing back.
A transcript saying “done” is not a substitute for current tests, review or accepted evidence. See long-task operations for waiting, budgets and continuation.
loopx statusshows the intended goal and a useful next action.- The chosen host has an active continuation mechanism and remains available.
- The task has an acceptance check, spending boundary and stopping rule.
- Merge, publication and other consequential operations retain explicit approval.
For examples rather than setup, explore the public application scenarios and long-horizon terminal study. Study results have task, model and budget limits; they do not guarantee a gain on every project.