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 linkfox-ai/linkfox-skills --skill linkfox-kalodata-tiktok-productgit clone --depth 1 https://github.com/linkfox-ai/linkfox-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/linkfox-ai/linkfox-skills/linkfox-kalodata-tiktok-product)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-kalodata-tiktok-product"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-kalodata-tiktok-product/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/linkfox-ai/linkfox-skills/linkfox-kalodata-tiktok-product"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-kalodata-tiktok-product.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 121 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00204 | $0.02674 |
| Opus 5 | $0.00102 | $0.01337 |
| Sonnet 5 | $0.00041 | $0.00535 |
| Haiku 4.5 | $0.00020 | $0.00267 |
Grade A, and why
linkfox-kalodata-tiktok-product 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kalodata - TikTok Product Search & Detail
This skill supports a two-step TikTok Shop product workflow via the Kalodata data source:
- Browse TikTok Shop product leaderboards to discover top-ranked and best-selling products.
- Fetch one product's full detail by
productId.
Use the ranking endpoint when the user wants best-seller rankings, hot products, or product discovery. Use the detail endpoint when the user already has a productId or has selected one product from a ranking result.
Core Concepts
The product ranking endpoint returns a paginated leaderboard filtered by region, dateRange, currency, language, and optional sortField. Each product row includes identity, price, sales volume, revenue (split across video, live, and showcase channels), revenue growth rate, commission rate, and launch date. Results are paginated with pageNumber (1-5) and pageSize (5-100).
The product detail endpoint fetches one TikTok Shop product by productId. It returns the product's price range, sales, revenue (with channel split), commission rate, launch date, review count, category hierarchy, owning shop, and associated video/live/creator counts. The productId usually comes from the ranking response field product_id.
Both endpoints may reflect a statistical delay (T+1). See references/api.md for full request and response details.
Data Fields
Ranking rows include:
| Field | Description |
|---|---|
| product_id | Product unique ID; pass this as productId for detail lookup |
| product_name | Product title |
| unit_price | Price per unit (currency follows region, e.g. USD for US) |
| sales_volumn | Units sold (field is spelled volumn) |
| revenue | Total revenue / GMV; equals video + live + showcase revenue |
| video_revenue | Revenue from the video channel |
| live_revenue | Revenue from the live-stream channel |
| showcase_revenue | Revenue from the showcase / 橱窗 channel |
| revenue_growth_rate | Revenue growth rate (%) |
| commission_rate | Commission rate as a direct percentage (25.0 = 25%) |
| launch_date | Product launch date (YYYY-MM-DD) |
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.
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.
- 9d ago First seen · 180 lines · 204 tokens per session scan A decfbb4b82bc
linkfox-kalodata-tiktok-product is a skill published in the GitHub repository linkfox-ai/linkfox-skills (101 stars, last pushed 22d ago), licensed MIT. It adds 204 tokens to every session and 2,674 once invoked, about $0.0010 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 2026-09-03.
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