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 skills add BingHanOfUESTC/open_agent_team --skill reader-impact-testgit 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/skills/binghanofuestc/open_agent_team/reader-impact-test)<a href="https://agentmods.dev/skills/binghanofuestc/open_agent_team/reader-impact-test"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/reader-impact-test/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/skills/binghanofuestc/open_agent_team/reader-impact-test"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/reader-impact-test.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 | $0.00041 | $0.00519 |
| Opus 5 | $0.00020 | $0.00260 |
| Sonnet 5 | $0.00008 | $0.00104 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
reader-impact-test 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 8d 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
Reader Impact Test
作家水准不是“文字看起来像文学”，而是读者在阅读过程中持续被牵引、相信、参与，并在结尾后仍然回想。
1. 读者体验曲线
检查每一段或每一场给读者带来的状态：
被钩住：我想知道下一步。
信任：我相信人物会这样做。
紧张：我知道某件东西正在失去。
参与：我在推断人物没说出口的东西。
回想：新信息让我重新理解前文。
流失：我开始跳读、等作者讲重点。
流失点比漂亮句子更重要。
2. P0 阅读流失点
以下问题属于 P0：
第一段没有任何压力或异常
前三页只有设定和气氛
人物行为不可信
关键冲突靠误会或降智成立
场景之间只有时间顺序，没有因果压力
结尾靠解释主题收束
读者读完无法复述故事独特之处
3. 记忆点测试
读完后应能记住至少一类：
一个无法替代的画面
一个带矛盾的人物选择
一句不是金句但暴露人物的对话
一个前后呼应的物件或动作
一个让人不舒服但成立的结尾余味
没有记忆点的故事，即使通顺，也不达标。
4. 结尾余震测试
好结尾通常做到：
事件结束，但意义没有结束。
答案落地，但情绪不被解释干净。
主角得到某物，同时失去某物。
最后一个细节让读者重新理解开头。
坏结尾通常是：
作者宣布主题
人物终于明白
反转与人物选择无关
为了温暖或残酷而强行收束
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.
- 8d ago First seen · 83 lines · 41 tokens per session scan A 17aa436068bf
reader-impact-test is a skill published in the GitHub repository BingHanOfUESTC/open_agent_team (106 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 519 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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