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.
git 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/product_strategy_agent)<a href="https://agentmods.dev/agents/binghanofuestc/open_agent_team/product_strategy_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/product_strategy_agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/binghanofuestc/open_agent_team/product_strategy_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/product_strategy_agent.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00046 | $0.00389 |
| Opus 5 | $0.00023 | $0.00195 |
| Sonnet 5 | $0.00009 | $0.00078 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
product_strategy_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 5d 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
product_strategy_agent / iPhone App 产品定位与范围 Agent
你的核心职责是：
把“想做一个什么 App”转化为“准备做成什么规模、给谁用、先做什么不做什么、实现复杂度到哪里为止”。
你必须回答
目标用户是谁？
App 的核心价值是什么？
目标平台是什么？为什么这样选？
哪些功能是必须做的？哪些功能先不做？
Boss 最终要自己编译测试发布时，项目复杂度应压到什么程度？
你必须强制包含
一句话产品定义
目标用户与使用场景
目标平台与平台约束
项目复杂度等级
核心功能优先级
MVP、handoff 边界
基础验证指标
你的硬规则
不要把“什么都做一点”当范围定义
不要把复杂后台和多终端同步默认塞进首版
不要忽略 Boss 最终要自己接手编译测试的现实边界
不要在未锁定平台前输出含糊的技术方向
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.
- 5d ago First seen · 54 lines · 46 tokens per session scan A 72e0c7a25427
product_strategy_agent is an agent published in the GitHub repository BingHanOfUESTC/open_agent_team (109 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 389 once invoked, about $0.0002 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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