菜单
Implement one ticket handed off by the orchestrator and open a PR for review.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | ticket-worker |
| description | Implement one ticket handed off by the orchestrator and open a PR for review. |
Implement the handed-off ticket. Follow the repository’s tracker instructions: confirm the ticket is unassigned, set Assigned-To to the supplied worker identity, and move it to in-progress.
Work only on this ticket. Follow its accepted contracts and the repository’s existing skills and conventions. Run the relevant checks and run_code_review.
Commit and push the changes, then open a PR against the supplied PR base using the creating-prs skill and gh pr create --base <supplied-pr-base>. Add the pi-orchestrated label and append the supplied PR marker exactly to the PR body.
Do not merge the PR or resolve the ticket; the orchestrator owns that.
Do not poll the PR or its checks. PR Watch will deliver CI results and review feedback. Address that feedback, run the relevant checks and run_code_review, then commit and push the fixes.
Coordinate parallel ticket workers as an event-driven control plane through repos worktrees, Pi sessions, delegated pull-request review, squash merges, and filesystem tracker frontiers. Use when orchestrating implementation tickets rather than implementing or reviewing one ticket directly.
Manage work in the local Tickets filesystem tracker. Use when the user asks to inspect, search, create, claim, update, move, rename, complete, or lint a Tickets project or ticket.
Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
Provides comprehensive code review guidance. Helps catch bugs, improve code quality, and give constructive feedback. Use when: reviewing pull requests, conducting PR reviews, code review, reviewing code changes, establishing review standards, mentoring developers, architecture reviews, security audits, checking code quality, finding bugs, giving feedback on code.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Use Datadog's MCP server through mcp2cli for agent-native Datadog investigation workflows: DDSQL, Kubernetes resource inspection, metric context/tag discovery, span/log/RUM attribute discovery and aggregation, monitor authoring/validation, dashboard widgets, notebooks, incidents, services, dependencies, and error tracking. Prefer pup-datadog-cli for stable scriptable Datadog API queries.
