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 bilibiligit 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/bilibili)<a href="https://agentmods.dev/skills/0xmariowu/autosearch/bilibili"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/bilibili/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/bilibili"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/bilibili.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 | $0.00000 | $0.00802 |
| Opus 5 | $0.00000 | $0.00401 |
| Sonnet 5 | $0.00000 | $0.00160 |
| Haiku 4.5 | $0.00000 | $0.00080 |
Grade A, and why
bilibili 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Attribution
Source: self-written, plan
autosearch-0418-channels-and-skills.md§ F002c.
name: bilibili description: Chinese tech video platform with tutorials, conference recordings, and uploader-authored articles, via TikHub. version: 1 languages: [zh, mixed] methods:
- id: via_tikhub impl: methods/via_tikhub.py requires: [env:TIKHUB_API_KEY] rate_limit: {per_min: 60, per_hour: 1000}
- id: api_search impl: methods/api_search.py requires: [] rate_limit: {per_min: 30, per_hour: 500} fallback_chain: [api_search, via_tikhub] when_to_use: query_languages: [zh, mixed] query_types: [tutorial-video, comparison, breakdown, tech-opinion] avoid_for: [text-only-query, academic-papers] quality_hint: typical_yield: medium chinese_native: true layer: leaf domains: [chinese-ugc] scenarios: [chinese-native, video-content, tutorial, tech-opinion] model_tier: Fast experience_digest: experience.md
Overview
Bilibili is a Chinese video platform with strong coverage in tutorials, hardware comparisons, software explainers, gaming, and creator-led technical commentary. It is useful when the user wants Chinese-language visual content rather than text-first references.
For autosearch coverage, this channel fills a gap between global video search and Chinese-native creator ecosystems. It matters because many Chinese tutorials, teardown videos, and side-by-side product breakdowns are published on Bilibili long before they appear elsewhere.
When to Choose It
- Choose it for Chinese tutorial-video and breakdown queries.
- Choose it for device comparisons, creator explainers, and tech-opinion in video form.
- Choose it when visual demonstration matters more than short text description.
- Prefer it over YouTube when the target audience, terminology, or creator ecosystem is Chinese-native.
- Avoid it for pure text lookup or formal academic paper search.
How To Search (Planned)
via_tikhub- Use TikHub's paid Bilibili general search API to retrieve mixed result groups, then map only video and article results into normalized evidence.via_tikhub- Strip Bilibili search-hit HTML markers, normalize uploader identity, and derive canonical video or article URLs frombvid/ article ids when needed.api_search- Call Bilibili search endpoints for videos and creators using Chinese or mixed query text, then rank by topical relevance and engagement.api_video_detail- Fetch richer metadata for shortlisted videos with authenticated detail access whencookie:bilibiliis available.api_video_detail- Normalize title, uploader, publish time, duration, play stats, and canonical video URL.
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 · 70 lines · 0 tokens per session scan A 6d14c4c0485b
bilibili is a skill published in the GitHub repository 0xmariowu/Autosearch (44 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 802 tokens. 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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