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 0xmariowu/Autosearch --skill wechat_channelsgit clone --depth 1 https://github.com/0xmariowu/AutosearchWrote 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/0xmariowu/autosearch/wechat_channels)<a href="https://agentmods.dev/skills/0xmariowu/autosearch/wechat_channels"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/wechat_channels/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/0xmariowu/autosearch/wechat_channels"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/wechat_channels.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00053 | $0.00365 |
| Opus 5 | $0.00026 | $0.00182 |
| Sonnet 5 | $0.00011 | $0.00073 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
wechat_channels 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 11d 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.
What it actually says
Search WeChat Channels (视频号) for Chinese-language short videos. Returns title, creator, duration, and video CDN URL.
Note: Video CDN URLs (findermp.video.qq.com) require WeChat session for download.
For transcription, use video-to-text skills on videos from supported platforms (bilibili/douyin/youtube).
MCP tool example
run_channel("wechat_channels", "Python机器学习教程", k=10)
Quality Bar
- ≥3 results with valid
wechat_channels:{creator}source - Title extracted, HTML tags cleaned
- Video URL returned for reference
What ships with it
3 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.
- 11d ago First seen · 43 lines · 53 tokens per session scan A 212a90afa455
wechat_channels is a skill published in the GitHub repository 0xmariowu/Autosearch (44 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 365 once invoked, about $0.0003 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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