An experimental workflow for finding and resuming coding runs interrupted by a host restart or automation failure. It checks original instructions, worktree ownership, and external state, then reports which runs were resumed, skipped, or held.
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Experimental workflow for finding and resuming interrupted coding runs. Use after an agent host restart or an interrupted automation.
安装前可以查看交给 AI 代理的指令内容。
Start with the Factory guide for workflow setup and configuration.
Read .agent-factory/config.yaml, the optional
skill_prompts.factory-recover entry, and the Factory configuration reference. Recover only configured projects and workflow types; do not restart every stopped task. The prompt cannot restore canceled work or grant new authorization.
List runs resumed, skipped, or held and the evidence for each decision. Follow the separate configured notification policy.
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Guide public skill additions and updates through file placement, catalog documentation, installation discovery, integration settings, and validation. Distinguish ordinary skills from instruction-based, app-backed, and generated skills so each receives the appropriate checks.
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Monitor another AI agent’s work and independently investigate the same task. Compare the original request with actual changes and test evidence, report gaps and concrete follow-up steps, and make limited fixes when authorized.
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Open Agent-Native apps beside the conversation through Dispatch MCP, a connection for app tools. Create or edit content using the current screen and selection, then read saved results back to confirm the changes.
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Organize large coding tasks with Claude Fable directing lower-cost subagents. Delegate bounded research, edits, and tests, then have Fable verify evidence, resolve conflicting findings, integrate changes, and review the final result.
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Organize work so an expensive AI model handles planning, judgment, and final review while cheaper helper agents perform bounded research, coding, and testing. Define ownership and verification requirements, then inspect the evidence and integrate their results centrally.
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Configure a software delivery workflow that turns selected feedback and maintenance signals into verified, reviewed changes. Define information sources, schedules, working directories, and separate permissions for actions such as implementation, merging, deployment, and notifications.
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