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-echotik-batch-product-detailgit 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-echotik-batch-product-detail)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-product-detail"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-product-detail/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-echotik-batch-product-detail"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-product-detail.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 84 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 | $0.00228 | $0.02395 |
| Opus 5 | $0.00114 | $0.01197 |
| Sonnet 5 | $0.00046 | $0.00479 |
| Haiku 4.5 | $0.00023 | $0.00239 |
Grade A, and why
linkfox-echotik-batch-product-detail 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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EchoTik TikTok Batch Product Detail
This skill guides you on how to fetch detailed performance metrics for a batch of TikTok Shop products, helping sellers and operators compare candidate products side-by-side using sales, GMV, live-stream, video, and influencer data.
Core Concepts
This tool retrieves full detail metrics for up to 1000 TikTok Shop products in a single call. You identify products by ID and/or by TikTok Shop product URL; the backend extracts the productId from each URL and merges it with any IDs you supplied, then returns per-product analytics.
Input options (at least one is needed; both can be combined):
productIds— array of TikTok product IDsproductUrls— array of TikTok Shop product URLs (e.g.https://shop.tiktok.com/us/pdp/<slug>/<productId>?...); the trailingproductIdis extracted from each URL
Multi-period metrics: Sales, GMV, live count, video count, influencer count, and views are each reported across 1d / 7d / 15d / 30d / 60d / 90d windows plus a cumulative total, so you can read both recent momentum and long-run totals.
Prices are in USD: minPrice, maxPrice, and spuAvgPrice are USD values.
Status flags (integers): salesTrendFlag — 0=stable, 1=rising, 2=falling; isSShop — fully-managed (全托管) shop; offMark — delisted; freeShipping — free shipping.
vs. search: This is detail lookup for known products (you already have IDs/URLs). To discover products by keyword, use linkfox-echotik-product-search; for new-product rankings use linkfox-echotik-new-product-rank.
Parameter Guide
| Parameter | Type | Required | Description | Default |
|---|---|---|---|---|
| productIds | array<string> | No* | TikTok product IDs (up to 1000 items) | - |
| productUrls | array<string> | No* | TikTok Shop product URLs; the productId is extracted from each and merged with productIds (up to 1000 items) |
- |
* At least one of productIds / productUrls must be provided; both can be passed together.
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.
- 12d ago First seen · 149 lines · 228 tokens per session scan A b8368d34346d
linkfox-echotik-batch-product-detail is a skill published in the GitHub repository linkfox-ai/linkfox-skills (101 stars, last pushed 22d ago), licensed MIT. It adds 228 tokens to every session and 2,395 once invoked, about $0.0011 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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