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 aronhy/tiktok-agent-skills --skill tiktok-lead-generation-operatorgit clone --depth 1 https://github.com/aronhy/tiktok-agent-skillsWrote 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/aronhy/tiktok-agent-skills/tiktok-lead-generation-operator)<a href="https://agentmods.dev/skills/aronhy/tiktok-agent-skills/tiktok-lead-generation-operator"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-lead-generation-operator/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/aronhy/tiktok-agent-skills/tiktok-lead-generation-operator"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-lead-generation-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.00727 |
| Opus 5.5 | $0.00019 | $0.00291 |
| Sonnet 5.5 | $0.00010 | $0.00145 |
| Haiku 4.5 | $0.00005 | $0.00073 |
Grade A, and why
tiktok-lead-generation-operator 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 2mo 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
TikTok 内容获客运营
开始任何分析前，完整读取 references/workflow.md 与 references/report-template.md。详细定义、边界和报告格式只以两份参考为准。
控制流程
边界请求优先于定制方案输入门槛：仅判断指标可计算性时，直接应用同一统计总体或可追踪 cohort、同一归因窗口和兼容来源系统规则。兼容来源系统是指事件位于一个系统内，或存在明确、可信、可审计的跨系统关联/归因方法；漏斗与 KPI 必须记录关联键/方法。只有纯禁止操作请求（仅要求抓取联系人或执行外联，不含其他合规定制规划）可绕过四项输入门槛；此时必须拒绝，并同时提供不依赖业务假设的自愿加入内容方向、一个 CTA、资格问题与仅供审核的回复草稿，四项缺一不可。混合请求若同时包含禁止操作和合规定制规划，先只拒绝禁止操作，再对合规部分执行以下输入门槛；有缺项时只问第一个缺项，不提供定制策略：
- 依次确认目标国家或地区、具体产品或服务、目标客户、期望私域动作及渠道。一次只问第一个未收到的问题，然后停止；“收到”仅限用户明确表述或所给 brief 无歧义说明。
- 未提供账号 URL 时使用从零模式；所有定位和内容结论均标为假设。提供 URL 时，先复用
$tiktok-account-audit的公开证据、来源账本与可信度规则，再做获客改造；绝不把公开互动推断成私域转化。 - 仅输出计划、可审阅的内容和回复草稿。不得发送私信、抓取或导入联系人、提交表单、发布内容，或改动任何外部账号。
- 以报告模板的固定十二节顺序交付，并为结论标注 A/B/C 可信度。
| 情况 | 处理 |
|---|---|
| 缺少必填输入 | 只问固定顺序中的第一个缺项并停止。 |
| 无账号 URL | 从零模式；将账号、受众和结果写为假设。 |
| 有账号 URL | 复用 tiktok-account-audit，仅采用已验证公开证据。 |
| Shop 为主目标 | 转交 $tiktok-shop-operator，不以本 Skill 为主流程。 |
| Shop 与线索并存 | 分开交易与线索路径；若影响方案，询问哪个业务结果优先。 |
缺项在用户明确说明无法提供某项但仍要求继续时，才给出带条件的有限框架，可信度为 C；“直接给方案”或“不要问问题”不等于无法提供，仍须只问第一个缺项并停止；不得伪装为定制正式报告。
What ships with it
3 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.
- 2mo ago First seen · 28 lines · 48 tokens per session scan A 778560daee2f
tiktok-lead-generation-operator is a skill published in the GitHub repository aronhy/tiktok-agent-skills (182 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 727 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
tiktok-lead-generation-operator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tiktok-lead-generation-operatoraronhy/tiktok-agent-skills | Skill | 182 | 3mo ago | MIT | A | 48 | Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |