Review a configured queue of pull requests, checking code changes, linked issues, tests, and review discussions. Report actionable findings and supporting evidence, then assess approval or merge separately against the permissions and conditions configured for each action.
中文简介正在准备中。当前显示英语简介。
Experimental workflow for reviewing configured repositories' pull requests. Use for manual or scheduled PR triage, approval, or merge decisions.
实测评分 未实测
查看安装方法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.
This skill reviews a filtered queue. For one long-lived, explicitly authorized
PR, use factory-babysit-pr. Read the filters and independent action policies
from .agent-factory/config.yaml; see the configuration reference.
Apply the optional skill_prompts.factory-review-prs entry as additional
project guidance; it does not replace this skill or authorize an action
disabled by policy.
For each candidate PR:
Unavailable or partial state is unknown, never a clean result.
| Action | Proceed only when |
|---|---|
| Review | The PR matches configured filters and has not already had the required current review. |
| Reply or other PR write | That action is enabled and its conditions hold. Use configured wording; do not tag, assign, or message otherwise. |
| Approve | Approval is enabled and author, risk, ownership, current-head, check, and review conditions are verified. |
| Merge | Merge is separately enabled; every live merge condition and any soak hold on the unchanged head. |
Host-level mergeability, one green check, or a bot approval does not prove all gates passed. Re-read the exact head and live state immediately before an approval or merge. Restart a configured soak if the head or a gate changes.
For each PR, state the decision and evidence. List skipped, unavailable, and held PRs with the reason. Keep review findings separate from approvals, replies, and merge decisions.
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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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。