Move a Claude Code task to a teammate without sharing a login

A developer outlined a Markdown-based task-handoff template that lets teams transfer Claude Code work between people without sharing provider logins, separating the roles of author, executor, and reviewer. The template specifies outcome, scope, starting ref, access boundaries, required evidence, and acceptance criteria, with the executor using their own authorized repository and Claude Code account. The writeup argues this preserves shared AI execution capacity while keeping each person's credentials and permissions separate.

A coding task often stalls because the person who wrote the brief cannot run it right now. Passing a provider login to someone else blurs who executed the work and what access they had. A better handoff transfers the task specification, then lets the next person work with their own authorized tools. Here is a small template for doing that. It works as a Markdown issue even if your team never adopts a task platform. Task: Add an empty-state message to the projects list Outcome When the API returns zero projects, show: “No projects yet. Create one to get started.” Scope - Change the projects-list component and its focused tests. - Keep loading and API-error states distinct from the empty state. - Do not change the API or create a project automatically. Starting point - Repository: <repo URL - Base branch or commit: <exact ref - Relevant paths: <component , <tests - Command to run: <project's documented test command Access - Author may write the brief and review the result. - Executor uses their own repository and Claude Code access. - Executor stops if either permission is missing. - No provider credentials, session cookies, or personal tokens are included. Evidence to return - Commit or pull-request URL - Files changed - Test command and actual output - Screenshot only if captured from the running app - Any untested behavior or remaining risk Acceptance A reviewer checks the empty, loading, and error states, then accepts or returns the task with specific changes. The exact repository paths and command belong in the real task. Leaving them vague forces the executor to rediscover scope and makes review harder. Suppose Maya prepares this brief but has no time to implement it. Arun has authorized access to the repository and uses his own Claude Code account. Maya gives Arun the task, not her login. Arun checks out the stated base ref, inspects the three UI states, edits the component, and runs the repository's documented tests. His delivery should identify the changed files and real commit, name the exact test command and result, and say whether he performed a visual check. Those details must come from the actual run. “Tests passed” is not acceptable unless the executor ran them and can identify the command that produced the result. Maya then reviews the diff and evidence. If the empty message appears while the API is still loading, she returns the task with that finding. If it meets the acceptance criteria, she accepts it. Delivery and acceptance are different events. This pattern gives a team shared AI execution capacity through transferable work while keeping each person's account and permissions separate. The author owns scope and acceptance criteria. The executor owns the work performed with their own authorized environment. The reviewer owns the verdict. A task system can preserve those boundaries and make the handoff easier to inspect; Wagglet's discussion of AI task handoffs https://wagglet.com/blog/close-team-skill-gaps-with-ai-task-handoffs is one example. The same discipline still matters in a plain issue tracker. It does not solve missing access, unclear requirements, or unreliable tests. When those are absent, improve the brief or stop the run. Borrowing another person's credentials is not a fix. This article was drafted with AI assistance.