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-chuhaijiang-tiktok-videogit 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-chuhaijiang-tiktok-video)<a href="https://agentmods.dev/skills/linkfox-ai/linkfox-skills/linkfox-chuhaijiang-tiktok-video"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-chuhaijiang-tiktok-video/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-chuhaijiang-tiktok-video"><img src="https://agentmods.dev/badge/skills/linkfox-ai/linkfox-skills/linkfox-chuhaijiang-tiktok-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00127 | $0.02275 |
| Opus 5.5 | $0.00051 | $0.00910 |
| Sonnet 5.5 | $0.00025 | $0.00455 |
| Haiku 4.5 | $0.00013 | $0.00228 |
Grade A, and why
linkfox-chuhaijiang-tiktok-video 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 1mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TikTok Video Market Intelligence
Use this skill to research public TikTok videos: discover videos with market filters, inspect one video's performance, identify products promoted by a shoppable video, or read its public comments.
Core Concepts
- This is a read-only public-market research skill. It does not upload, publish, edit, or delete TikTok videos.
- Search returns
data.items[]plusdata.total_count. Reuse an item'sidfor detail, product, or review drill-downs. - Detail returns the main profile in
data.items[];include=coreadditionally returns normalized performance metrics indata.core.items[]. - Related-product and review rows use endpoint-specific prefixed fields. Read
references/api.mdbefore interpreting them. - Money-like values can be objects such as
{ "unit": "US", "value": 402056 }. Preserve the returned unit and value; do not treat them as plain numbers or silently convert currency. - Always preserve the returned
country_code. Do not relabel a row solely from the requested marketplace.
Data Fields
| Field | Meaning |
|---|---|
id |
Video, product, or comment identifier for the current endpoint |
video_desc |
Video caption or description |
share_url |
Public TikTok URL |
author_id / author_unique_id |
Creator identifiers |
video_play_count / video_like_count |
Lifetime plays and likes |
video_comment_count / video_share_count / video_collect_count |
Engagement counts |
video_engagement_rate |
Returned decimal engagement rate; format as a percentage only when clearly labeled |
video_30d_gpm |
30-day GMV per thousand views; not a percentage |
data.core.items[] |
Optional normalized core metrics from detail include=core |
tiktok_video_detail_product_* |
Product and video-commerce fields from related products |
tiktok_video_detail_comment_* |
Comment identity, text, author, likes, replies, and timestamp |
Endpoints
| User goal | Endpoint | Script |
|---|---|---|
| Search public videos | /chuhaijiang/videos/search |
chuhaijiang_video_search.py |
| Inspect one video | /chuhaijiang/videos/detail |
chuhaijiang_video_detail.py |
| Find products promoted by a video | /chuhaijiang/videos/related-products |
chuhaijiang_video_related_products.py |
| Read video comments | /chuhaijiang/videos/reviews |
chuhaijiang_video_reviews.py |
What ships with it
7 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.
- references/api.md 11 KB
- references/onboarding.md 2.0 KB
- scripts/chuhaijiang_video_detail.py 12 KB runs code
- scripts/chuhaijiang_video_related_products.py 12 KB runs code
- scripts/chuhaijiang_video_reviews.py 12 KB runs code
- scripts/chuhaijiang_video_search.py 12 KB runs code
- scripts/onboarding.py 24 KB runs code
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.
- 1mo ago First seen · 119 lines · 127 tokens per session scan A 70bef7513636
linkfox-chuhaijiang-tiktok-video is a skill published in the GitHub repository linkfox-ai/linkfox-skills (109 stars, last pushed 2d ago), licensed MIT. It adds 127 tokens to every session and 2,275 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-15.
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