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-category-strategygit 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-category-strategy)<a href="https://agentmods.dev/skills/aronhy/tiktok-agent-skills/tiktok-category-strategy"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-category-strategy/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-category-strategy"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-category-strategy.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 | $0.00046 | $0.01050 |
| Opus 5 | $0.00023 | $0.00525 |
| Sonnet 5 | $0.00009 | $0.00210 |
| Haiku 4.5 | $0.00005 | $0.00105 |
Grade A, and why
tiktok-category-strategy 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 13d 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 类目策略
基于可追溯的商品、店铺、视频、达人和官方趋势证据，判断一个 TikTok/TikTok Shop 类目的进入条件，并形成运营策略；不把缺失数据、单个爆款或行业传闻写成市场事实。
先加载参考
在调用工具或下结论前，必须完整读取：
需要选择 KSS MCP 工具、参数、返回字段或关联方式时，再读取共享的 ../tiktok-shop-operator/references/mcp-tools.md。实际连接的 MCP schema 始终优先于该参考。
控制流程
- 确认目标类目和目标国家或地区。两者都是初始必需输入。首次发现任一项缺失时，只问一个最高优先级问题并停止：若类目缺失，只问“目标类目是什么？它决定研究对象、商品映射和内容比较范围。”；否则只问“目标国家或地区是什么？它会改变趋势、价格、政策和竞争格局。”同一回复不得附带框架、策略、go/no-go、市场主张或报告，即使用户在该次请求中要求继续。
- 只有在完成上述提问后，用户后续明确表示无法或不愿提供该输入、并再次要求继续时，才可按报告参考输出“通用/条件性部分框架”。不得调用依赖缺失维度的实时研究工具或页面，不得给出市场特定事实、go/no-go、价格、政策或竞争主张；必须列出缺失输入及影响、分开标示假设、给出 C 级低可信度，并说明仍被阻断的研究与结论。
- 记录可选条件：价格带、账号类型、商业目标、预算、内容语言和计划周期。不要把未给出的条件补成行业基准、固定内容数量、视频时长、达人层级或效果阈值。
- 两个必需输入齐全时，按工作流规范化类目和市场，用
product_search建立候选商品池，再以shop_search、video_search、creator_search和代表视频的caption_extract补齐相互关联的证据。保留对象 ID、地区、币种、统计窗口、分页范围和停止原因。 - 以 TikTok Creative Center 的同地区、同类目公开趋势作为当前官方补充；它不可访问、需登录、受地区限制或字段不足时明确记录，不能用搜索摘要、记忆或其他网页冒充其数据。
- 仅在目标类目和目标市场均已提供后，才完成允许的重试、分页、ID 关联和公开浏览器读取，再检查证据完整性。此后的关键取证缺失会改变进入结论、切入方向或合规判断时，只问一个问题；用户要求继续时可提供带影响范围和 A/B/C 可信度的部分报告。
- 只有跨来源且口径可比的证据才能支持进入、竞争、需求、内容或达人结论。结果前置：先按报告模板给“是否建议进入”和三个优先动作，后给证据、明细、限制和风险；把观察、推断、假设和待验证项分开写。
输出边界
- 两个必需输入齐全时使用固定的十二节报告模板；标明目标市场、收集时间、筛选条件、样本/页数、来源、完整性、默认值、缺失字段和可信度。输入缺失的后续拒绝例外只能使用报告参考中的受限部分框架，不能伪装成正式报告。
- 不混淆播放量、销量、销售额、商品价格、视频发布时间和统计窗口；不跨地区、币种或不兼容周期合并排名。
- 不编造 KSS 字段、Creative Center 趋势、政策要求、链接、成功调用、配额状态或量化行业基准。没有返回的字段写“未提供”；浏览器无法读取写“读取失败”或“未公开”。
- 不绕过登录、验证码、反爬、地域限制或访问控制；不保存或回显 API Key、Token、Cookie 或其他凭证；不发布、投放、下单、改店或联系达人。
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.
- 13d ago First seen · 35 lines · 46 tokens per session scan A 724beba33b3e
tiktok-category-strategy is a skill published in the GitHub repository aronhy/tiktok-agent-skills (152 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 1,050 once invoked, about $0.0002 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 2026-08-30.
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