Delegate coding tasks to external CLI agents with Codex as controller.
npx skills add https://github.com/logicrw/agpair --skill agpair-codex
Please help me install this Agent Skill. Skill: agpair-codex Source: https://github.com/logicrw/agpair/tree/main/skills/Codex Command: npx skills add https://github.com/logicrw/agpair --skill agpair-codex
AGPair-codex solves the problem of handling complex coding tasks that require external assistance, such as implementation candidates, alternative analysis, or verification evidence, by integrating with Codex and leveraging external CLI agents.
Start a task with AGPair-codex using the following command:
agpair task start \
--repo-path "$REPO" \
--controller codex \
--executor grok-cli \
--task-kind quick_review \
--wait-policy lease \
--authorization-profile local_readonly \
--completion-policy report \
--body "$BRIEF"
High-intent search queries and answers about installing and using this skill.
You can delegate complex coding tasks to external CLI agents by using a controller like Codex to route implementation, code review, and testing work while managing the execution budget and gathering verification evidence.
Automating code review and testing is best handled by a fusion-style workflow that fans out parallel lane tasks to external CLI agents, using a controller to synthesize results and gate the final implementation.
Yes, Codex can act as the controller and verifier for asynchronous coding tasks, maintaining control over the workflow through managed hooks, bounded implementation slices, and completion reporting.
Fusion-style workflow fanout works for code implementation by routing bounded, isolated slices of work to parallel lanes, synthesizing the outputs at specific nodes, and passing them through controller gates for verification.
You need to define an authorization profile, such as local_readonly, and a wait policy, like lease, when starting a task to ensure the external agent executes within the correct access and execution boundaries.
You should use a routing budget for task delegation when executing complex workflows that require parallel or asynchronous fanout, ensuring optimization of task execution and controlled evidence gathering across multiple agents.
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