100x-persona

100x-persona is a skill for Claude Code from kezd088/100x-skill-tiktok. It costs 119 tokens per session (1,870 once invoked), scanned A, original, MIT.

A script-analysis tool that chooses who should deliver an advertisement and where it should be filmed, with each choice tied to exact words in the script.

In plain words
What is it for?
Use it to create a person-and-setting plan for a TikTok or user-generated-content script. It accepts written scripts, not video files.
Why use it?
It makes the character and setting traceable to the supplied copy, reducing unsupported guesses about the speaker, audience, or scene.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the 100x-skill-tiktok plugin — 9 skills shipped together

Good fit Use it to create a person-and-setting plan for a TikTok or user-generated-content script. It accepts written scripts, not video files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kezd088/100x-skill-tiktok/100x-persona
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 kezd088/100x-skill-tiktok --skill 100x-persona
Clone the repo
git clone --depth 1 https://github.com/kezd088/100x-skill-tiktok

Made for: Claude Code.

Or install 100x-skill-tiktok, the plugin that ships this one along with the rest of its 9 skills.

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 100x-persona

README.md
[![agentmods](https://agentmods.dev/badge/skills/kezd088/100x-skill-tiktok/100x-persona/github.svg)](https://agentmods.dev/skills/kezd088/100x-skill-tiktok/100x-persona)
Your own site
<a href="https://agentmods.dev/skills/kezd088/100x-skill-tiktok/100x-persona"><img src="https://agentmods.dev/badge/skills/kezd088/100x-skill-tiktok/100x-persona/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 100x-persona

Your own site · 80×15
<a href="https://agentmods.dev/skills/kezd088/100x-skill-tiktok/100x-persona"><img src="https://agentmods.dev/badge/skills/kezd088/100x-skill-tiktok/100x-persona.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,870 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.
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 $0.00119 $0.01870
Opus 5 $0.00060 $0.00935
Sonnet 5 $0.00024 $0.00374
Haiku 4.5 $0.00012 $0.00187

Measured 12d ago against content hash bc118f1b0c71, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

100x-persona 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate.js), 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/100x-persona/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

100x-persona

一句话定位

输入一段脚本/文案纯文本,输出"谁来讲"(人物)+ "在哪讲"(场景,独立实体,非人物附属 字段)+ 两者如何与脚本原句绑定,三者都能逐字回指原文。属于 100x 体系 L2 创意生成层, 对应"3.1 人物×场景"这一步。

何时触发

用户说:

  • "给这条脚本配个人设" / "这条脚本谁来讲比较合适" / "这个人设怎么定"
  • "这个场景怎么设定" / "这条广告适合什么场景拍" / "这条脚本在哪拍合适"
  • "who should deliver this script" / "what persona fits this product"
  • "what setting fits this ad" / "where should this be filmed"
  • 或直接给一段脚本文案,要求"配人物和场景" / "assign a character and setting"

输入

最小输入(类别 A,必填):source_script——完整脚本/文案纯文本。本 skill 不接视频 文件,只吃文本。

上游可选产出(类别 C,缺失静默跳过,不阻塞,也绝不要求用户先跑别的 skill): 100x-segment 产出的 segments[](若存在,pairings[].segment_ref 可回填,缺失时 整个字段省略,靠 script_span_quote 独立定位)。

输出

结构见 schema.jsonPersonaSceneBundle = source_script(原文回显,供证据核对)+ personas(人物 map,独立实体)+ scenes(场景 map,独立实体,与 personas 平级, 不是人物的字符串字段)+ pairings(人物×场景×脚本原句的绑定表)+ meta。可选再渲染 一张人类可读的 Markdown 摘要(人物列表 / 场景列表 / pairing 对照表)。

核心约束(4 条公理,详见 axioms.md

  1. 场景是独立实体,靠 ID 引用,不是人物的内嵌字段——personas/scenes 是两个平级 map, pairings[] 里的 persona_ref/scene_ref 必须真实存在于对应 map(引用完整性)
  2. 人物的权威/受众依据必须是原文逐字子串,不许臆造——authority_evidence_quote / audience_pain_quote / script_span_quote 都要能在 source_script 里逐字找到。 已知局限(不是隐藏缺陷):逐字子串只能证明"这句话原文有",证明不了"这句话在 人物字段里的语义方向没被反着用"——比如摘一句自我怀疑的话("如果你不信我")反着当 权威锚点,也是合法子串。当前机制包含一层闭集自我怀疑短语检测(命中即要求人工披露, 见 axioms.md 公理2),但反讽/引用-驳斥框架类反转仍检测不到,这是字符串匹配的 天花板,详见 axioms.md 公理2"机制天花板与缓解措施"段
  3. 场景须具体到微观坐标,不许写泛地点——闭集泛化词表拒收 + 至少 2 件具体道具
  4. 人物与场景零孤儿,建了必须被至少一个 pairing 引用——不为了"看起来矩阵齐全"堆砌

三阶段流程

详见 workflow.md:Phase 1 人物反推(扫描脚本里的 Authority/Pain 信号,逐字摘取证据句) → Phase 2 场景建模(每个场景线索独立建实体 + 与人物/脚本原句绑定 + 零孤儿自检)→ Phase 3 输出(组装 JSON,公理 1-4 全过)。

独立调用保证

类别 A(source_script)缺失 → 固定拒绝话术追问,不代猜、不接视频文件替代。类别 C (上游 100x-segment 产出)缺失 → 静默跳过,绝不要求用户先跑其他 skill

禁用词

让我 / 希望 / 或许 / 大概 / 可能 / 也许 / 让我们;AI 客服味(as an AI / I'd be happy to / feel free to);不编造脚本原文没有的资质/认证/见证/效果数据;不写死任何客户品类词典; micro_coordinate 不使用闭集泛化词(见 axioms.md 公理 3:某处/随便/某个地方/TBD/ somewhere/anywhere 等)。

Read the full file on GitHub · 99 lines

Files

What ships with it

11 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. 12d ago First seen · 99 lines · 119 tokens per session scan A bc118f1b0c71

Subscribe to this mod's changes

100x-persona is a skill published in the GitHub repository kezd088/100x-skill-tiktok (8 stars, last pushed 16d ago), licensed MIT. It adds 119 tokens to every session and 1,870 once invoked, about $0.0006 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens