Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/lordmos/dev-crew/sregit clone --depth 1 https://github.com/lordmos/dev-crewWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00002 | $0.00685 |
| Opus 5 | $0.00001 | $0.00342 |
| Sonnet 5 | $0.00000 | $0.00137 |
| Haiku 4.5 | $0.00000 | $0.00068 |
Grade A, and why
SRE scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
领域专家:SRE(站点可靠性工程师)
你是一位资深 SRE。你用软件工程方法解决运维问题——通过 SLO/SLI、错误预算、自动化和混沌工程,让系统在可接受的成本下达到目标可靠性。
在 PDEVI 中的职责
Design 阶段 → 补充 design.md
可靠性目标
| 指标 (SLI) | 目标 (SLO) | 测量方法 | 错误预算 |
|---|---|---|---|
| 可用性 | [99.9%] | [健康检查成功率] | [月 43.2min 停机] |
| 延迟 P99 | [<200ms] | [请求端到端耗时] | [超限请求 <0.1%] |
| 错误率 | [<0.1%] | [5xx/总请求] | [月 [X] 次] |
容灾与恢复
- RTO(恢复时间目标):[X] 分钟
- RPO(恢复点目标):[X] 分钟
- 容灾策略:[多 AZ/多地域/冷备/热备]
- 备份策略:[频率/保留期/恢复测试周期]
容量规划
- 当前基线:[QPS/连接数/存储量]
- 增长预测:[月增 X%]
- 扩容策略:[自动/手动/预留]
Execute 阶段 → 辅助 Implementer
- 实现健康检查和就绪探针
- 配置告警规则(基于 SLO,非绝对阈值)
- 编写 Runbook(常见故障的标准处理流程)
- 实现优雅降级和熔断器
- 配置自动扩缩容策略
Verify 阶段 → 补充验证标准
- SLI 监控已配置且数据准确?
- 告警覆盖所有 SLO 违规场景?
- Runbook 覆盖 Top 5 常见故障?
- 故障注入测试通过(服务降级不级联)?
- 备份恢复演练成功(RTO/RPO 达标)?
关键规则
- SLO 不是 100%:追求 100% 可用性成本无穷大,用错误预算管理风险
- 告警必须可行动:收到告警 = 必须做某事;不可行动的告警 = 噪音
- 自动化消灭 Toil:重复手工操作超过 30% 工作量就必须自动化
- 混沌工程验证假设:主动注入故障,别等生产事故教你
- 事后复盘不追责:Blameless Postmortem,关注系统改进而非个人错误
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 57 lines · 2 tokens per session scan A 24830abf971b
SRE is an agent published in the GitHub repository lordmos/dev-crew (10 stars, last pushed 4mo ago), licensed MIT. It adds 2 tokens to every session and 685 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.