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shipcli

Not a new chat entry point.
The control layer for AI CLIs in your terminal.

When teams plug into multiple AI CLIs at once, the real mess is not the models. It is install, switching, fallback, recovery, and audit trails. shipcli pulls those fragmented actions into one stable execution chain.

See the Flow See the Control Layer
  • Unify install, upgrade, auth, and health checks
  • Unify routing, fallback, recovery, logs, and execution state
  • Built for developers and teams running multiple AI CLIs
ship run "fix webhook retry and replay flow"
control shipcli install / auth / doctor / route / resume
workers codex / claude / gemini / qwen Split work by task, route it by health and policy 
$ ship doctor
codex         ready       152ms
claude-code   ready       181ms
gemini-cli    degraded    auth refresh needed
qwen-code     ready       166ms
resume-store  healthy

$ ship route "add tests for payment callback failures"
read-repo     -> codex
edit-patch    -> claude-code
run-verify    -> local pytest
fallback      -> qwen-code if edit timeout
summary       -> shipcli merge-output

$ ship run --resume
[01] doctor         done
[02] route          done
[03] patch          done
[04] verify         failed
[04] verify         resumed from checkpoint
[05] report         done

The Problem

More CLIs do not just mean more options. They create a full extra layer of maintenance and recovery cost.

01

Maintenance gets fragmented

Every CLI comes with its own install flow, upgrade cycle, auth state, and environment dependencies. The overhead adds up fast.

02

Task switching gets messy

Reading repos, editing code, running verification, and writing summaries often means manually hopping across CLIs. The flow breaks apart.

03

Recovery becomes fragile

Without shared checkpoints and persisted execution state, one interruption can force the team to rebuild the workflow from memory and screenshots.

Control Layer

shipcli does not replace any model. It pulls every CLI into one reliable control surface inside the terminal.

01

Environment

Standardize the baseline operations

Unify install, upgrade, auth, and health checks first, so the team stops losing time to tool-specific infrastructure drift.

  • install
  • upgrade
  • auth
  • doctor
02

Routing

Orchestrate by task and runtime state

shipcli decides who handles each step based on task type, CLI health, timeouts, fallback policy, and execution budget.

  • route
  • fallback
  • policy
  • budget
03

Recovery

Catch failures and keep the history

Execution state, logs, exit codes, artifacts, and checkpoints are persisted together, so failures do not force a full restart.

  • resume
  • logs
  • status
  • artifacts

Execution Flow

What matters is how a task gets routed, fails, falls back, resumes, and leaves behind a clear execution record.

Step 01

Run doctor before you run anything else

Check CLI availability, auth freshness, and resume-store health before execution starts, so obvious failures are removed up front.

Step 02

Route the work instead of hand-switching

Distribute repo reading, code edits, verification, and summaries across different executors based on task type and routing policy.

Step 03

Recover from failure without replaying everything

Step-level state is persisted continuously. Timeouts, network issues, or expired auth can resume from the nearest checkpoint.

Step 04

Keep a traceable record, not a screenshot trail

Logs, exit codes, artifacts, fallback reasons, and final summaries are saved together, so teams can review the real execution chain.

Built For

Built for developers and teams already working across multiple AI CLIs.

If you only use one CLI, the switching cost may still be small. Once multiple tools enter the stack, shipcli is there to reduce the chaos around maintenance, switching, recovery, and auditability.

Individual developers

For people who want one stable workflow across several CLIs instead of stitching it together by hand.

Small engineering teams

For teams that need one operational layer for environment setup, task recovery, and persistent execution state.

Heavy toolchain users

For operators already using multiple AI CLIs and wanting policy, fallback, and audit behavior in one layer.

Final CTA

Bring multiple AI CLIs into one execution chain.

shipcli is not another chat box. It adds a real operational control layer to multi-CLI work inside the terminal.

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