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-video-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-video-detail)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-video-detail"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-video-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-video-detail"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-echotik-batch-video-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 123 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 | $0.02979 |
| Opus 5 | $0.00114 | $0.01489 |
| Sonnet 5 | $0.00046 | $0.00596 |
| Haiku 4.5 | $0.00023 | $0.00298 |
Grade A, and why
linkfox-echotik-batch-video-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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EchoTik TikTok Batch Video Detail
This skill batch-fetches detailed performance metrics for TikTok videos you already have IDs or URLs for, helping sellers and marketers compare videos side-by-side using views, likes, comments, shares, video sales/GMV, and creator data.
Core Concepts
This tool retrieves full detail metrics for a batch of TikTok videos in a single call. You identify videos by ID and/or by TikTok video URL; the backend extracts the videoId from each URL and merges it with any IDs you supplied, then returns per-video analytics.
Input options (at least one is needed; both can be combined):
videoIds— array of TikTok video IDs (up to 1000)videoUrls— array of TikTok video URLs (e.g.https://www.tiktok.com/@<unique_id>/video/<videoId>orhttps://www.tiktok.com/video/<videoId>); the trailingvideoIdis extracted from each URL and merged withvideoIds(up to 1000)
Multi-period metrics: views and likes are each reported as a cumulative total plus 1d / 7d / 30d increments, so you can read both lifetime performance and recent momentum.
Engagement & attribution: comments, shares, favorites, estimated video sales (units), and estimated video sales GMV (amount) are returned per video.
Flag fields (salesFlagText / isAdText / createdByAiText): human-readable 是/否 (AI: 是/否/未知) labels for selling / ad / AI-generated videos.
vs. search: This is detail lookup for known videos (you already have IDs/URLs). To discover videos by region/filter (no IDs needed), use linkfox-echotik-list-video.
Data Fields
| Field | Type | Description |
|---|---|---|
| videoId | string | 视频ID |
| videoDesc | string | 视频描述/文案 |
| officialUrl | string | TikTok官方视频地址 |
| coverUrl | string | 视频封面URL |
| duration | integer | 视频时长(秒) |
| width | string | 视频宽度(px) |
| height | string | 视频高度(px) |
| ratio | string | 视频清晰度(如 540p/720p) |
| dataSize | string | 视频文件大小 |
| createDate | string | 视频发布日期(yyyy-MM-dd HH:mm:ss) |
| userId | string | 达人ID |
| uniqueId | string | TikTok账号ID(unique_id) |
| avatar | string | 达人头像URL |
| totalViewsCnt | integer | 总播放量 |
| totalViews1dCnt | integer | 近1天播放量增量 |
| totalViews7dCnt | integer | 近7天播放量增量 |
| totalViews30dCnt | integer | 近30天播放量增量 |
| totalDiggCnt | integer | 总点赞数 |
| totalDigg1dCnt | integer | 近1天点赞增量 |
| totalDigg7dCnt | integer | 近7天点赞增量 |
| totalDigg30dCnt | integer | 近30天点赞增量 |
| totalCommentsCnt | integer | 总评论数 |
| totalSharesCnt | integer | 总分享数 |
| totalFavoritesCnt | integer | 总收藏数 |
| totalVideoSaleCnt | integer | 视频销量(件,估算) |
| totalVideoSaleGmvAmt | integer | 视频销售GMV(估算金额) |
| salesFlagText | string | 是否带货视频(是/否) |
| isAdText | string | 是否投流视频(是/否) |
| createdByAiText | string | 是否AI视频(是/否/未知) |
| productCategoryList | string | 关联商品分类(JSON字符串,空为[]) |
| videoProducts | string | 视频带货商品(JSON字符串,空为[]) |
| region | string | 视频所在区域代码 |
| sourceType | string | 数据来源(如 Tiktok) |
| sourceTool | string | 来源工具(如 EchoTik-视频列表) |
What ships with it
4 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 · 187 lines · 228 tokens per session scan A 8667a0771f17
linkfox-echotik-batch-video-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 2,979 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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