tiktok-shop-operator

tiktok-shop-operator is a skill for Codex from aronhy/tiktok-agent-skills. It costs 73 tokens per session (989 once invoked), scanned A, original, MIT.

A skill for researching TikTok Shop, the shopping service built into TikTok. It searches products, shops, videos, and creators, extracts captions, and combines related results into evidence-based plans.

In plain words
What is it for?
Use it to find products, analyse shops, study viral shopping videos, match creators, extract video captions, and build research-backed actions.
Why use it?
It reduces the manual work of finding comparable products, competitors, sales content, and potential creators while keeping search conditions and missing data visible.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to find products, analyse shops, study viral shopping videos, match creators, extract video captions, and build research-backed actions.

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Install with agentmods
npx agentmods add skills/aronhy/tiktok-agent-skills/tiktok-shop-operator
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 aronhy/tiktok-agent-skills --skill tiktok-shop-operator
Clone the repo
git clone --depth 1 https://github.com/aronhy/tiktok-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 tiktok-shop-operator

README.md
[![agentmods](https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-shop-operator/github.svg)](https://agentmods.dev/skills/aronhy/tiktok-agent-skills/tiktok-shop-operator)
Your own site
<a href="https://agentmods.dev/skills/aronhy/tiktok-agent-skills/tiktok-shop-operator"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-shop-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.

agentmods 80×15 button for tiktok-shop-operator

Your own site · 80×15
<a href="https://agentmods.dev/skills/aronhy/tiktok-agent-skills/tiktok-shop-operator"><img src="https://agentmods.dev/badge/skills/aronhy/tiktok-agent-skills/tiktok-shop-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 989 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 $0.00073 $0.00989
Opus 5 $0.00036 $0.00495
Sonnet 5 $0.00015 $0.00198
Haiku 4.5 $0.00007 $0.00099

Measured 12d ago against content hash 4428c011fe1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

tiktok-shop-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 12d 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.

skills/tiktok-shop-operator/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TikTok Shop Operator

Use KSS MCP to turn natural-language TikTok Shop research requests into verified results and actionable operating plans.

Load References

  1. Read references/mcp-tools.md before choosing tools, parameters, joins, or return fields.
  2. Read references/workflows.md for operational or multi-step tasks.
  3. Read references/output-templates.md before presenting results.
  4. Read references/examples.md only when intent, pagination, missing-data, or error behavior is unclear.

Do not duplicate detailed tool schemas in this file.

Interpret the Request

  1. Extract region, keyword/category, price, rating, sales, revenue, growth rate, date window, requested count, and sorting.
  2. Preserve every explicit user condition.
  3. Ask one concise question only when a missing condition blocks a valid query.
  4. Use an MCP default only when valid, and disclose it in the query scope.
  5. Identify whether the task needs one tool or a cross-tool workflow.

Choose Tools

  • Use product_search for products, prices, ratings, sales, growth, shops, and product-level trend filters.
  • Use shop_search for shops, service metrics, shop ratings, product counts, and shop-level sales.
  • Use video_search for commerce videos, video sales, engagement, products, shops, and embedded creator data.
  • Use creator_search for creator discovery and creator metrics.
  • Use caption_extract for captions from a specific TikTok video URL.

Use IDs for joins. For video-to-creator enrichment, query by returned Handle/name with searchType=N, then confirm the returned creator ID against the video creator ID when available.

Execute Safely

  1. Query the smallest useful scope first.
  2. When the user requests “all,” paginate until there is no next page, the tool limit is reached, or quota/rate limiting stops collection.
  3. Never call the first page “all results.”
  4. Deduplicate paginated objects by their stable ID.
  5. Apply the user's sort. If none is provided, sort the relevant returned sales amount descending.
  6. Do not invent an orderField value absent from the reference. Sort locally within the disclosed collected scope when necessary.
  7. Keep regions, currencies, and time windows separate.
  8. Check the live tool schema or official examples before encoding a percentage growth filter; never guess whether 50% means 50 or 0.5.
  9. Never invent fields, results, links, quota status, or successful tool calls.
  10. Write missing fields as “未提供.”
  11. Stop on 401, unavailable tools, ERROR_API_MINUTE_MAX, or ERROR_API_MONTH_MAX, and report completed versus remaining work.
  12. Do not silently broaden filters after an empty result. Suggest one relaxation and wait for approval.

Read the full file on GitHub · 78 lines

Files

What ships with it

5 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 · 78 lines · 73 tokens per session scan A 4428c011fe1c

Subscribe to this mod's changes

tiktok-shop-operator is a skill published in the GitHub repository aronhy/tiktok-agent-skills (152 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 989 once invoked, about $0.0004 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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