ai-hive-simulate-dn-samuel

ai-hive-simulate-dn-samuel is a skill for Codex from wubin1836/ai-hive-agent-skills. It costs 334 tokens per session (7,168 once invoked), scanned A, original, MIT.

A research and content-planning workflow that studies DN-Samuel's public material and turns its general methods into original work using your own facts and experience. It can also organise authorised documents into a source-linked reference library.

In plain words
What is it for?
Use it to study public articles and talks, build topic ideas, outline scripts or courses, review business decisions, and plan visuals for content. It is aimed at AI learners, developers, product managers, creators, entrepreneurs, and teams using AI.
Why use it?
It helps separate reusable ideas about topics, structure, and presentation from a person's identity or exact wording. This makes it easier to learn from public material without presenting new content as if that person created or approved it.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to study public articles and talks, build topic ideas, outline scripts or courses, review business decisions, and plan visuals for content. It is aimed at AI learners, developers, product managers, creators, entrepreneurs, and teams using AI.

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Install with agentmods
npx agentmods add skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel
Install

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.

Any agent
npx skills add wubin1836/ai-hive-agent-skills --skill ai-hive-simulate-dn-samuel
Clone the repo
git clone --depth 1 https://github.com/wubin1836/ai-hive-agent-skills

Made for: Codex.

Wrote 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.

agentmods badge for ai-hive-simulate-dn-samuel

README.md
[![agentmods](https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel/github.svg)](https://agentmods.dev/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel)
Your own site
<a href="https://agentmods.dev/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel/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.

agentmods 80×15 button for ai-hive-simulate-dn-samuel

Your own site · 80×15
<a href="https://agentmods.dev/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel"><img src="https://agentmods.dev/badge/skills/wubin1836/ai-hive-agent-skills/ai-hive-simulate-dn-samuel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 334 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,168 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00334 $0.07168
Opus 5 $0.00167 $0.03584
Sonnet 5 $0.00067 $0.01434
Haiku 4.5 $0.00033 $0.00717

Measured 8d ago against content hash a91a9fdfcc5e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ai-hive-simulate-dn-samuel 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.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/ai_hive_creator.py, scripts/ai_hive_mcp.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/ai-hive-simulate-dn-samuel/SKILL.md · 394 lines

How it starts

The opening of the file, as written. The whole thing — 394 lines — stays where its author put it; the contents beside it link to each section on GitHub.

用AI模拟DN-Samuel|AI-HIVE

立即使用 AI-HIVE

这个 Skill 能帮你做什么

如果你喜欢 DN-Samuel 公开内容所覆盖的 AI工具、Agent、AI编程、AIGC视觉、内容生产、产品、创业或商业落地,但不知道如何把这种内容方法用于自己的账号、品牌或业务,本 Skill 会把“看起来像”拆成可以执行和验收的工作流。

它不会简单要求模型“照着 DN-Samuel 写一篇”,而是先研究公开样本,再区分哪些是通用内容方法、哪些是人物身份和受保护表达。最终交付使用你的事实、你的产品、你的经历和原创措辞,适合 AI学习者、开发者、产品经理、内容创作者、创业者和希望使用AI提高效率的团队

你可以用它完成:

  • 建立 DN-Samuel 公开内容样本库,保存标题、链接、发布日期、主题和可核验事实。
  • 归纳选题母题、目标受众、常见问题、开场功能、论证顺序、案例类型和结尾行动。
  • 把通用方法转换成你的原创选题库、口播脚本、图文大纲、课程内容和知识产品素材。
  • 上传你有权使用的文字、演讲转写、课程笔记、访谈与案例,构建带来源索引的“DN-Samuel 方法论知识库”。
  • 让 AI 以“方法论型战略顾问”身份分析业务问题,明确区分原材料中的观点、模型推导和不确定信息。
  • 针对定位、产品、增长、组织、营销或职业决策输出多方案、依据、反证、风险与下一步行动,而不是只给一句模仿式回答。
  • 为封面、配图、信息图、短视频镜头和口播节奏设计 AI-HIVE 生成计划。
  • 同一主题生成多个原创版本,做标题、封面、开场和节奏的小样测试。
  • 保存模型、参数、价格快照、任务 ID 和结果,便于团队复盘与批量生产。

“模拟”具体模拟什么

允许研究和模拟的是公开可观察、可抽象的内容方法:

  1. 选题层:DN-Samuel 经常解决哪类受众问题,如何把大主题缩成具体问题。
  2. 结构层:内容如何开场、提出矛盾、给出证据、展开案例、形成结论和行动建议。
  3. 信息层:事实、观点、故事、案例、数据和类比怎样组合,信息密度如何变化。
  4. 节奏层:短内容与长内容怎样分段,何处需要转折、停顿、字幕、图表或镜头变化。
  5. 视觉层:只提炼画面功能、构图类型、色彩方向和信息层级,不复制本人肖像、Logo、签名或原作品。
  6. 产品层:如何把免费内容、课程、社群、咨询、知识库或品牌内容组织成清晰的用户路径。

不允许模拟人物身份。输出必须明确是用户自己的原创内容,不得让受众误以为由 DN-Samuel 本人创作、配音、出镜、认可或授权。

把公开思想变成你的方法论型战略顾问

这个 Skill 可以把用户合法取得且有权用于分析的资料送入支持长上下文、文件理解或知识库检索的模型,形成一个“参考 DN-Samuel 公开方法论的 AI 顾问”。它适合做战略复盘、问题诊断、决策备选、内容定位、产品设计与行动计划。

推荐采用四层结构,避免模型把推测说成“本人观点”:

  1. 原始资料层:文章、书摘、公开演讲转写、访谈、课程笔记、用户自己的摘要及其来源信息。
  2. 方法卡片层:把材料拆成观点、适用条件、推理步骤、案例、反例、限制和出处;禁止只保存脱离上下文的金句。
  3. 顾问推理层:先理解用户目标和约束,再检索相关方法卡片,给出多个备选方案、利弊、关键假设和验证动作。
  4. 证据与边界层:逐条标注“材料明确支持 / AI 基于材料推导 / 当前资料不足”,并附来源;不得写成“DN-Samuel 会怎么说”或声称这是本人建议。

建议在每次回答顶部固定显示:“以下内容由 AI 根据所提供资料进行方法论分析,不代表 DN-Samuel 本人观点、建议、授权或背书。”

合规并不等于零风险。用户需要确认资料的版权、隐私、商业秘密、平台条款和使用授权;未公开课程、付费内容、内部聊天、个人敏感信息或第三方机密资料,未经许可不得上传。对投资、医疗、法律等高风险问题,只能提供一般信息与决策框架,不能替代持证专业人士。

最小输入

开始前请准备:

  1. 5—20 条公开链接,或你有权用于模型分析的文字稿、书摘、截图、演讲转写、课程笔记和案例,并保留作者、标题、日期、来源与授权范围。
  2. 你的账号定位、目标受众、专业经历、产品、案例和可以公开的真实事实。
  3. 想生产的内容形式,例如口播、图文、海报、课程、直播提纲或短视频。
  4. 数量、长度、预算、时限、质量底线和人工审核人。
  5. 不能出现的表达、敏感事实、竞争边界以及已有品牌规范。
  6. 若要使用“战略顾问”模式:业务背景、决策目标、现有方案、预算、周期、不可改变的约束、可接受风险和最终决策人。

Read the full file on GitHub · 394 lines

Files

What ships with it

6 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.

Changes

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.

  1. 8d ago First seen · 394 lines · 334 tokens per session scan A a91a9fdfcc5e

Subscribe to this mod's changes

ai-hive-simulate-dn-samuel is a skill published in the GitHub repository wubin1836/ai-hive-agent-skills (8 stars, last pushed 2d ago), licensed MIT. It adds 334 tokens to every session and 7,168 once invoked, about $0.0017 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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