When tackling complex engineering problems, developers often switch between coding agents: for instance, starting architectural planning in Claude Code and then attempting algorithmic refactoring or test generation in Codex or a different model. However, dumping raw conversation logs into a new agent clutters its context with obsolete hypotheses, wasting tokens and developer time.
Switching between models is effective only when based on a formalized, portable handoff card and a focused verification step, rather than attempting to transfer unbounded chat transcripts.
1. Comparing Shifts: Model vs. Tool vs. API Provider
Do not confuse three fundamentally different operations:
| Dimension | Changing Model inside Agent | Switching Tool (Claude Code ↔ Codex) | Changing API Provider |
|---|---|---|---|
| What Changes | Model ID parameter in config | CLI client, protocol, and tool orchestration | Endpoint, Base URL, and authentication key |
| Task Context | Retained within current session | Full session reset; requires clean handoff | Retained in local environment config |
| API Protocol | Anthropic or OpenAI (Unchanged) | Transition from Anthropic Messages to OpenAI Responses API | Configuring Base URL and API key group |
| Recommended Scenario | Quick reasoning level upgrade | Testing alternative hypotheses in clean worktree | Routing through local or dedicated gateways |
2. Scenario-Based Tool Selection
Choose the best approach based on your current task requirements:
- Option 1 (Claude Code): Recommended if you need interactive codebase exploration, complex multi-file architectural refactoring, and flexible shell tooling.
- Option 2 (Codex CLI / Custom Provider): Best chosen if you require deterministic test generation, direct execution over OpenAI-compatible Responses API, or an independent second opinion on a committed diff.
3. The Portable Handoff Protocol
To transfer task state reliably without prompt clutter, author a structured handoff card containing only verified facts:
### Task Handoff: Database Connection Pool Limits
- **Goal**: Enforce max_connections=20 and add a 5s connection acquisition timeout.
- **Current State**: Branch `perf/db-pool-limits` created; modified `config/database.go`.
- **Verified Progress**: Test `go test ./config -run TestPoolLimits` passes.
- **Unresolved Blocker**: Under `wrk` load, pool exhaustion crashes without returning HTTP 503.
- **Target Check for Next Agent**: Implement 503 error handling on pool timeout and verify with a test.
[!IMPORTANT]
Zero Secrets Policy: Never include API keys, auth tokens, or.envcontents inside handoff cards. Each CLI tool reads its credentials from local environment variables. Check the setup guides for Claude Code and Codex in BetterToken Docs.
4. Step-by-Step Switching and Verification
Follow this 5-step procedure when handing work off to another agent:
-
Step 1: Checkpoint Git state. Review and stash uncommitted changes:
git status --short, then save the structured handoff card. - Step 2: Launch a fresh session. Start the secondary agent in an isolated Git worktree or clean terminal window.
- Step 3: Provide only the handoff card. Give the new agent the task goal and verification step without legacy chat history.
-
Step 4: Execute the focused verification check. Require the agent to run the target test and inspect changed files:
git diff --check. - Step 5: Decide based on observable output. If the secondary model solves the blocker cleanly, continue in that branch; otherwise, return to the primary session with zero regression overhead.
This approach prevents prompt bloat and turns model switching into an objective, measurable engineering experiment.
Originally published on the BetterToken blog.
BetterToken provides pay-as-you-go access to AI model APIs through
OpenAI-compatible and Anthropic-compatible endpoints — useful if you are wiring
Claude Code, Codex, or your own tooling to a custom base URL.
See the docs to get started.
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