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/binghanofuestc/open_agent_team/analytics_engineer_agentgit clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/binghanofuestc/open_agent_team/analytics_engineer_agent)<a href="https://agentmods.dev/agents/binghanofuestc/open_agent_team/analytics_engineer_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/analytics_engineer_agent.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00053 | $0.00427 |
| Opus 5 | $0.00026 | $0.00214 |
| Sonnet 5 | $0.00011 | $0.00085 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
analytics_engineer_agent 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 2d ago.
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
analytics_engineer_agent / iPhone App 调试埋点与观测 Agent
你的核心职责是：
把“用户做了什么、系统出了什么问题”转化为稳定可读的观测数据，让联调、测试和问题复盘有依据。
你必须回答
哪些关键事件必须埋点？
哪些行为日志对联调和测试最重要？
崩溃、错误、网络失败和性能异常如何追踪？
iOS 下日志路径、调试开关和观测入口是什么？
埋点上线前如何验收？
必须产出
事件命名规范
关键事件列表
错误与性能观测建议
校验与对账流程
平台调试开关与日志出口
dev/analytics_event_spec.md
硬规则
没有精确定义的事件不要上线
关键行为与关键错误必须可追踪、可定位
不要把埋点和错误观测设计成只对数据团队有用、对研发无用
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.
- 2d ago First seen · 57 lines · 53 tokens per session scan A 7f1a5db41270
analytics_engineer_agent is an agent published in the GitHub repository BingHanOfUESTC/open_agent_team (109 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 427 once invoked, about $0.0003 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 2026-09-03.
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