菜单
Monitor CI conservatively with snapshot-first status checks and actionable failure triage. Use when tracking pipeline runs, investigating build failures, or validating PR readiness.
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
Run a full deep-dive, evidence-first codebase audit and convert findings into prioritized sprint plans with implementation-ready task documents. Use when you need comprehensive architecture, quality, risk, and delivery planning from current code and docs.
Run a SplitBrain.AI LLM council review for high-impact decisions. Use when evaluating architecture tradeoffs, orchestration design, schema changes, retrieval/search behavior, agent governance, or long-term infrastructure decisions.
Submit a pull request, request review, triage comments, fix issues, and use bounded wait checks before merge and cleanup. Use when implementation is complete and the branch is ready for PR handling end to end.
Audit and reconcile drift between agent/prompt docs and actual runtime capabilities in SplitBrain.AI services, controllers, and MCP endpoints.
Run an agent self-review for skill and prompt improvements. Use periodically to audit skill design, token-cost hotspots, and workflow upgrades across the SplitBrain.AI customizations.
Shared core workflow for SplitBrain.AI task execution: scope, evidence, minimal-change implementation, validation, and tracking updates.
| name | ci-status-monitor |
| description | Monitor CI conservatively with snapshot-first status checks and actionable failure triage. Use when tracking pipeline runs, investigating build failures, or validating PR readiness. |
| argument-hint | Branch/commit and monitoring strictness |
| user-invocable | true |
| disable-model-invocation | false |
Inherits from task-core-loop.
Use this skill to monitor CI with clear, conservative status handling.
task-core-loop evidence and output discipline.gh run list --branch <branch> or gh run view for a specific run.