Codex Fable5
baskduf/FableCodex
Apply a Claude Fable 5 inspired operating style inside Codex.
当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。
Install Persona Design
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install kangarooking/system-prompt-skills persona-design --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/persona-design .claude/skills/persona-design && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .claude/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/kangarooking/system-prompt-skills/tree/main/persona-designType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install kangarooking/system-prompt-skills persona-design --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/persona-design .agents/skills/persona-design && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .agents/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install kangarooking/system-prompt-skills persona-design --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/persona-design .cursor/skills/persona-design && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .cursor/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/kangarooking/system-prompt-skills.git --path persona-design--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install kangarooking/system-prompt-skills persona-design --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/persona-design .gemini/skills/persona-design && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .gemini/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install kangarooking/system-prompt-skills persona-designInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/persona-design .github/skills/persona-design && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .github/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kangarooking/system-prompt-skills --skill persona-design -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install kangarooking/system-prompt-skills persona-design --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/system-prompt-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/persona-design .opencode/skills/persona-design && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "persona-design" agent skill from https://github.com/kangarooking/system-prompt-skills/tree/main/persona-design into .opencode/skills/persona-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "persona-design", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
persona-design- GitHub stars
- 207
- Token cost
- ~956 tokens
- SKILL.md length
- 327 words
- Files
- 1
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- MIT
At a glance
当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。
- Works in 4 steps: 角色声明 (Role… → 能力边界 (Capability… → 行为修饰符 (Behavioral… → …
- 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问你是谁
- SKILL.md covers R — 原文 (Reading), I — 方法论骨架 (Interpretation), A1 — 案例分析 (Past Application) and A2 — 触发场景 (Future Trigger) ★, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Persona Design is an agent skill from kangarooking/system-prompt-skills. 当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。 不适用于：纯人格风格调优（应使用 personality-system）、安全规则制定（应使用 safety-guardrails）、工具集成（应使用 tool-specification）。 关键 trigger 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问"你是谁"。
Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Prompt engineering and LLM guardrails. It works with OpenAI. The repository describes itself as: 从 165 个顶级 AI 产品系统提示词中蒸馏出的 15 个可执行 Agent skill. The licence is MIT.
When your agent uses it
- 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问你是谁
- Tasks that involve Prompt engineering
- Tasks that involve LLM guardrails
Example prompts
- “/persona-design”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 角色声明 (Role Declaration)：明确"你是什么"——名称、技术谱系、核心定位。这是身份的锚点，不可省略。
- 能力边界 (Capability Boundary)：定义"你能做什么"和"你不能做什么"——隐性或显性地划定行动范围。
- 行为修饰符 (Behavioral Modifiers)：用形容词短语定义"你如何行事"——温暖、直接、精确、幽默等风格标签。
- 关系框架 (Relationship Framing)：定义"你和用户是什么关系"——助手、教练、伙伴、代理、编辑等关系隐喻。
What it can do on your machine
Read from SKILL.md and the folder at commit 252cd52. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Persona Design loads about 956 tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 327 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from kangarooking/system-prompt-skills at commit 252cd52, republished under its MIT licence (© kangarooking). 327 words, ~956 tokens.
Download SKILL.mdSave it as
.claude/skills/persona-design/SKILL.md (or your agent's skills folder).- name
- persona-design
- description
- 当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。 不适用于：纯人格风格调优（应使用 personality-system）、安全规则制定（应使用 safety-guardrails）、工具集成（应使用 tool-specification）。 关键 trigger 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问"你是谁"。
- tags
- persona, identity, role-design, system-prompt
- related_skills
- personality-system, safety-guardrails
身份与人格定义模式 (Persona Design)
R — 原文 (Reading)
"You are Claude Opus 4.6, the most advanced model in the Claude family. Warm, kind, and honest." — Claude Opus 4.6 "You are ChatGPT, a large language model trained by OpenAI." — GPT-4o (with Personality v2) "You are Codex, based on GPT-5. You are running as a coding agent." — Codex "You are an expert designer." — Claude Design "You are Sparky, a teaching assistant." — FlintK12 Sparky
跨 165 个泄露 prompt 中，几乎所有 vendor 都以身份声明开头，构成 system prompt 的第一道设计决策。
I — 方法论骨架 (Interpretation)
身份定义由四个正交维度构成，形成一个可组合的身份矩阵：
- 角色声明 (Role Declaration)：明确"你是什么"——名称、技术谱系、核心定位。这是身份的锚点，不可省略。
- 能力边界 (Capability Boundary)：定义"你能做什么"和"你不能做什么"——隐性或显性地划定行动范围。
- 行为修饰符 (Behavioral Modifiers)：用形容词短语定义"你如何行事"——温暖、直接、精确、幽默等风格标签。
- 关系框架 (Relationship Framing)：定义"你和用户是什么关系"——助手、教练、伙伴、代理、编辑等关系隐喻。
这四个维度的不同组合产生截然不同的用户体验，即使底层模型完全相同。
A1 — 案例分析 (Past Application)
案例 1: Codex 的编程代理身份
- 问题: GPT-5 作为通用模型，如何在编程场景中建立足够的专注度和行动力？
- 设计模式的使用: Codex 将身份精确定义为 "running as a coding agent"，角色声明中嵌入了行动模式（agent 而非 assistant），能力边界隐含在 "based on GPT-5" 的技术谱系中。还通过 dirty worktree awareness 等细节强化了"我是开发者工具"的自我认知。
- 结论: 身份声明中的 agent 而非 assistant 一词差异，直接影响了模型在遇到模糊指令时是主动推理还是等待澄清。
案例 2: FlintK12 Sparky 的教学助手身份
- 问题: AI 在教育场景中既需要专业性又需要亲和力，如何平衡？
- 设计模式的使用: "Sparky" 这个名字本身传递了活力与亲近感，而 "teaching assistant" 的角色声明将关系框架定位为辅助者而非权威。配合 "School Duty of Care" 的安全层和 pedagogical memory 的记忆系统，形成了一个完整的教育角色。
- 结论: 名字选择（Sparky vs Academic AI）直接影响 K-12 学生群体的接受度和互动意愿。
案例 3: Claude Chrome 的分层身份
- 问题: Claude 作为浏览器扩展需要同时扮演导航者、操作者和安全守卫。
- 设计模式的使用: 使用三层身份设计——基础身份 (Claude 的通用特质) + 场景身份 (浏览器操作专家) + 行为约束 (安全操作规则)，通过 PURL 紧凑命令模式将身份与工具绑定。
- 结论: 分层身份比单一身份更能处理复杂场景中的角色冲突。
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 从零开始设计一个新 AI 产品的 system prompt
- 将通用模型适配到垂直场景（医疗、法律、教育、编程等）
- 需要让 AI 在不同子产品中保持品牌一致性但有差异化
- 用户反馈"AI 不知道自己是谁"或"角色混乱"
语言信号
- "帮我写一个 AI 助手的角色设定"
- "我们的 AI 产品需要一个身份定义"
- "如何让模型知道自己能做什么不能做什么"
- "不同场景下 AI 应该怎么介绍自己"
与相邻 skill 的区分
- 与
personality-system的区别: persona-design 定义"你是谁"（身份），personality-system 定义"你什么风格"（性格叠加层）。身份是骨骼，性格是外衣。 - 与
safety-guardrails的区别: persona-design 中可能包含能力边界声明（"我不会 X"），但这是角色定位而非安全防护。真正的安全规则应使用 safety-guardrails。
E — 可执行步骤 (Execution)
步骤 1: 确定角色声明
- 写下 AI 的名称、技术谱系（基于什么模型）、核心定位（用一句话说它是什么）
- 完成标准: 任何人读到这句话都能理解这个 AI 的核心用途
步骤 2: 定义能力边界
- 列出 AI 擅长的 3-5 个核心能力领域
- 列出 AI 明确不覆盖的领域（用正面表述而非否定句）
- 完成标准: 能力边界与产品实际功能完全对齐，没有过度承诺
步骤 3: 选择行为修饰符
- 从候选列表中选择 2-4 个形容词（温暖/直接/精确/简洁/幽默/严肃/专业/亲和等）
- 确保修饰符之间不矛盾（如"幽默且严谨"需要明确定义边界）
- 完成标准: 修饰符能在示例对话中一致体现
步骤 4: 设定关系框架
- 明确 AI 与用户的关系隐喻：助手/教练/伙伴/代理/编辑/顾问
- 在关系框架中定义主动权分配：AI 是等待指令还是主动建议
- 完成标准: 关系框架能指导 AI 在模糊场景下做出一致的决策
步骤 5: 组装并验证
- 将四个维度组装为完整的身份段落，确保顺序为：角色声明 → 能力边界 → 行为修饰符 → 关系框架
- 用"你是谁"测试验证：向 AI 提问"你是谁"，检查回答是否与身份定义一致
- 完成标准: AI 的自我介绍与定义完全吻合，且在不同追问方式下保持一致
B — 边界 (Boundary) ★
不要在以下情况使用此 skill
- 只需要调整语气风格而不改变角色定位（使用 personality-system）
- 需要定义安全规则和拒绝策略（使用 safety-guardrails）
- 需要设计工具接口和调用规范（使用 tool-specification）
- 产品是纯 API 服务而非对话式 AI（身份定义的重要性降低）
常见失败模式
- 身份膨胀: 在角色声明中塞入过多细节，导致核心定位模糊。应保持一句话的核心定位，细节分散到其他段落。
- 修饰符矛盾: 选择相互冲突的修饰符（如"谦逊且自信"），但没有定义触发边界。
- 关系框架缺失: 只定义"是什么"但不定义"和用户的关系"，导致 AI 在需要主动判断时无所适从。
- 照搬竞品身份: 直接复制其他产品的身份定义而不适配自己的场景，导致身份与能力不匹配。
- 忽略"我是谁"测试: 身份定义写得很漂亮但从未测试 AI 是否真的按此自我介绍。
© kangarooking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in persona-design of kangarooking/system-prompt-skills.
Open the folder on GitHubat commit 252cd52
Compare with similar skills
Persona Design next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Persona Design this skillkangarooking/system-prompt-skills | 207 | — | ~956 | Automated safety check: Pass | MIT | |
| Codex Fable5baskduf/FableCodex | 437 | — | ~1.6k | Automated safety check: Pass | AGPL-3.0 | |
| System Prompt Writing Guidecashew-labs/libretto | 904 | — | ~570 | Automated safety check: Pass | MIT | |
| Prompt Engineering Guidetreylom/prompt-engineering-skills | 185 | — | ~485 | Automated safety check: Pass | Custom licence | |
| AI Engineerkid-sid/claude-spellbook | 190 | — | ~3.7k | Automated safety check: Pass | MIT | |
| Implementation Strategyopenai/openai-guardrails-js | 105 | — | ~951 | Automated safety check: Pass | MIT |
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Personality System
kangarooking/system-prompt-skills
当需要在基础身份之上叠加可切换的人格风格层时调用此 skill。典型场景包括：为同一产品提供多种人格选项（如 GPT-5.1 的 friendly/professional/quirky 模式）、设计人格切换机制、防止人格泄露到用户内容中。
Safety Guardrails
kangarooking/system-prompt-skills
当需要为 AI 系统设计多层安全防线、内容过滤策略和伦理边界时调用此 skill。典型场景包括：设计拒绝策略与升级机制、防御 prompt 注入攻击、实现领域特定安全规则（教育、医疗、金融等）、定义 AI 的价值观锚点。
Tool Specification
kangarooking/system-prompt-skills
当需要为 AI 定义工具接口、设计调用规范、实现工具发现与编排机制时调用此 skill。典型场景包括：设计 AI agent 的工具集、定义 JSON Schema/XML/TypeScript 格式的工具描述、实现工具权限控制与并行调度、设计子代理委托架构。
Agent Delegation
kangarooking/system-prompt-skills
当系统提示词需要设计多代理协作架构、子代理专业化分工、代理间上下文隔离与传递机制、任务生命周期管理时调用此 Skill。适用于 AI Agent 平台、多工具编排系统、代码审查流水线、跨应用协作场景等。不适用于：单代理系统（无委派需求）、简单工具调用（无子代理概念）、纯 API 编排（无 AI 决策）。当需求聚焦于"单代理内的对话路由"而非"多代理间的任务分配"时，应该用…
Citation System
kangarooking/system-prompt-skills
当系统提示需要设计引用格式、信息溯源机制、来源标注系统时调用。适用于文档问答、搜索增强生成（RAG）、代码引用、浏览器辅助等需要让用户追溯信息来源的场景。不适用于纯创作类输出（如故事、诗歌），不适用于无需溯源的常识问答，也不适用于注入防御（虽然两者都涉及内容可信度）。
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Questions about Persona Design
What does Persona Design do?
当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。. Persona Design is an agent skill from kangarooking/system-prompt-skills.
When should I use Persona Design?
Persona Design fits situations like: 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问你是谁; tasks that involve Prompt engineering; tasks that involve LLM guardrails.
How do I install Persona Design in Claude Code?
Run `npx skills add kangarooking/system-prompt-skills --skill persona-design -a claude-code`. Or copy the skill folder (persona-design in kangarooking/system-prompt-skills) into .claude/skills/persona-design in your project. Claude Code loads it when a task matches its description.
How do I install Persona Design in Codex?
Run `npx skills add kangarooking/system-prompt-skills --skill persona-design -a codex`. Or copy the skill folder (persona-design in kangarooking/system-prompt-skills) into .agents/skills/persona-design in your project. Codex loads it when a task matches its description.
Can I use Persona Design in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kangarooking/system-prompt-skills --skill persona-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/persona-design, .gemini/skills/persona-design, .github/skills/persona-design and .opencode/skills/persona-design in your project.
What does Persona Design need to run?
SKILL.md names no scripts, command-line tools or credentials: Persona Design is instructions for the agent only.
Does Persona Design access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Persona Design safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Persona Design use?
Persona Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Persona Design use?
About 956 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Persona Design?
Skills that share tags, products or a category with Persona Design: Codex Fable5 (baskduf/FableCodex, 437 stars), System Prompt Writing Guide (cashew-labs/libretto, 904 stars), Prompt Engineering Guide (treylom/prompt-engineering-skills, 185 stars) and AI Engineer (kid-sid/claude-spellbook, 190 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Persona Design?
kangarooking (a GitHub user) maintains it in kangarooking/system-prompt-skills, which has 207 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on May 4, 2026.
Source: kangarooking/system-prompt-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.