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 open-octo/octo-agent --skill reader-simulationgit clone --depth 1 https://github.com/open-octo/octo-agentWrote 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/open-octo/octo-agent/reader-simulation)<a href="https://agentmods.dev/skills/open-octo/octo-agent/reader-simulation"><img src="https://agentmods.dev/badge/skills/open-octo/octo-agent/reader-simulation/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/open-octo/octo-agent/reader-simulation"><img src="https://agentmods.dev/badge/skills/open-octo/octo-agent/reader-simulation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 3 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 13 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00136 | $0.01335 |
| Opus 5 | $0.00068 | $0.00668 |
| Sonnet 5 | $0.00027 | $0.00267 |
| Haiku 4.5 | $0.00014 | $0.00134 |
Grade A, and why
reader-simulation 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 7d 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
Skill: reader-simulation
扮演用户指定的读者画像，像这个读者第一次读到这篇稿子那样去读，报告真实的 阅读体验。这不是技术性的批评，是"读起来是什么感觉"——哪里被吸引住了、 哪里开始走神、哪里犯糊涂、什么问题一直悬在脑子里没解决。
前置：明确读者画像
用户应该给出：读者对这个主题的熟悉程度、读者的阅读习惯/耐心、读者的年龄 或受众群体（如果相关）、读者对模糊/未解释术语的容忍度、这个读者已经知道 什么/不应该知道什么。
如果用户没给读者画像，先说清楚自己假设的是什么样的读者，再开始读。 不要用一个"通用读者"的反应来代表所有读者——不同的读者画像会读出完全不同 的体验。
方法
从头读到尾。通过下面几个"读者获得感"的通道追踪阅读体验：
- 可信度与说服力：论证有没有让人信服，还是读到某处开始怀疑作者的 依据？留意哪里让你点头认同、哪里让你想问"这个结论是怎么来的"、哪里 一个不成立的例子让你对前面的内容也开始怀疑。
- 理解摩擦点：哪里需要回读才能跟上、哪里一个术语没解释就用上了、 哪里代词指代不清、哪里逻辑跳跃让人跟不上。留意"我需要停下来想一下" 发生的具体位置。
- 情感共鸣：（如果这篇文章带叙事/个人经历成分）哪里让你感同身受、 哪里的描述让你觉得隔靴搔痒、哪里的情绪表达和内容本身对不上。
- 好奇心与追随欲：想不想知道接下来会讲什么、一个悬念/问题有没有 被解答、解答得太早还是太晚、什么时候开始不关心接下来讲什么了。
- 阅读心流：读起来是不是顺畅、想不想继续读下去、哪里需要强迫自己 才能读下去、哪里难度突然变化（太密集、太简单、或者表达不清导致 节奏被打断）。
不是每个通道都需要平均着墨——哪里体验明显就多写哪里。长文章尤其要注意 中段——这是注意力最容易变薄的地方。
按阅读顺序报告体验：哪里被吸引住了、哪里走神了、心里悬着什么问题、 这些问题什么时候变化了。停留在"正在阅读"的状态里，不要变成技术批评家 ——读者模拟的价值就是这种真实的阅读感受，而不是"技术上哪里有问题"。
把每个判断锚定到文本：具体段落位置、简短引用，说明是哪句话产生了这种 体验。
开头先说整体读下来是什么感觉、哪几个通道信号最明显。结尾补充这几个通道 之外、作者应该听到的其他反馈。
边界
- 不越界变成结构诊断或逐句批评。 报告的是"读起来是什么感觉"，不是
"哪里有技术性问题"——技术性诊断用
structural-diagnosis，逐段文字 打磨用line-polish。如果读的过程中发现了结构性问题，可以提一句 "这可能是个结构问题，建议跑一下 structural-diagnosis"，但不要在这个 技能里展开分析。 - 不代表"所有读者"。 报告的是指定画像这一个读者的体验，不是普适 结论。如果用户想知道不同读者群体的反应差异，分别跑几次、换不同画像。
- 不用来证明作者对或错。 一个读者觉得某处读不懂，这是真实的信号， 但不代表这处一定要改成这个读者能懂的样子——作者可能就是在写给另一类 读者。报告体验，判断权在作者。
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 78 lines · 136 tokens per session scan A c63e7a0a3198
reader-simulation is a skill published in the GitHub repository open-octo/octo-agent (97 stars, last pushed yesterday), licensed MIT. It adds 136 tokens to every session and 1,335 once invoked, about $0.0007 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.
Other skills, from other repositories
ha-mac-control
Hope Agent native macOS desktop control — the standard maccontrol status / diagnostics / apps / dock / spaces / snapshot / visual / windows / menu / clipboard / dialog loop, target-first action rules, no-blind-coordinate policy, and recovery for stale AX/window/menu/dialog state. Load whenever using maccontrol, or…
ha-skill-creator
Create, edit, improve, or audit Hope Agent skills. Use when the user wants to: (1) create a new skill from scratch, (2) edit or improve an existing skill, (3) review or clean up a SKILL.md file, (4) run evaluations to test skill effectiveness, (5) optimize skill descriptions for better trigger accuracy. Trigger…
ha-browser
Hope Agent browser automation — the standard status → tabs → snapshot → act loop, stale-ref recovery rules, and what to do when login / 2FA / captcha / camera-prompt / dialog blocks progress. Load this skill whenever you reach for the browser tool. Trigger on: user asks the agent to open / control / click / scrape /…
ha-logs
A read-only troubleshooting skill for querying Hope Agent’s local SQLite databases, which store logs, conversations, and background-job status.
ha-pet-import
Safely import, select, switch, or enable a compatible desktop pet in Hope Agent. Resolve packages from any origin, including local folders, zip archives, pet.json plus a sprite, PNG/WebP atlases, chat attachments, repository or cloud files, direct HTTPS artifact URLs, and download pages. Use whenever a user asks to…
feishu
A toolkit for working with Feishu, also called Lark, a workplace collaboration platform. It covers documents, spreadsheets, files, wikis, approvals, calendars, and contacts.