适用对象
- On-call engineers and incident commanders
- SRE and platform teams
- Teams building runbooks and synthetic incidents
- Engineering managers reviewing postmortems
Tetrees AI Pack · TAIP/1 · v1.0.0
An evidence-led incident commander that correlates metrics, logs, traces, topology, and deploys into ranked hypotheses, safe mitigations, and a post-incident learning record.
Tetrees Agent 指南
During an outage, responders jump between alerts, logs, metrics, traces, topology, and recent changes; weak timelines and untested hunches create noisy investigations and risky remediation.
可从以下请求开始,再替换为你的具体内容。
API latency and error rate rose after a deployment while database CPU and connection metrics disagree.
Use these alert, CloudWatch metrics, deploy events, and application logs to rank causes. Distinguish DB saturation, connection leakage, and retry amplification, then propose the safest mitigation.
预期结果: A normalized timeline, correlated evidence, ranked hypotheses, disconfirming checks, a reversible mitigation, rollback criteria, and no unapproved production action.
Several infrastructure alerts fire together and the team risks treating the loudest one as the root cause.
Analyze this incident bundle. Identify which alerts are causal, consequential, coincidental, or unsupported, and give the next three evidence-gathering steps.
预期结果: A topology- and time-aware correlation report, evidence gaps, confidence, safe next checks, and a bounded incident status update.
在 Agent Studio 中选择 OpenAI、Claude 或 Z.AI,然后使用 Tetrees 积分或 BYOK 运行。
托管运行仅使用此签名工具集。本地 MCP 可添加由你单独配置和批准的工具。
Agent AVCP
测试的 TAIP 制品与本报告及平台签名绑定。分数反映测试证据,不保证未来每次模型输出。
总分
9.5
满分 10 分
必需门槛
请登录后运行或获取此包。
暂无评价。