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Bilibili video summary

Skill kiakun-collab/kiakun-skills/skills/bilibili-video-summary

Kiakun 的 AI Agent Skills 集合(Claude Code / OpenClaw / 通用 SKILL.md):HTML→可编辑 PPTX、图片型 PPT 重构、GPT Image 2 出图、小红书/B站自动化、文件夹向量知识库、游戏 UI 与玩家互动设计等 10+ 技能。

Install
npx -y skills add kiakun-collab/kiakun-skills --skill bilibili-video-summary

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

B站视频决策助手。当用户发送B站视频链接时,拉取视频信息、字幕正文、弹幕、热评与官方AI小结, 由脚本预消化为统计信号,再生成"值不值得看/看哪段/评论共识争议"的决策导向总结。 触发条件:用户发送B站视频链接(BV号、AV号或完整URL)时自动触发。

SKILL.md

4.9 KB, as published. Nobody here has run it

B站视频决策助手

你(Claude)是总结者,脚本只负责取素材。 脚本以最低成本拿全原始文本素材 + 预算好的统计信号, 输出一份 ≤15KB 的固定量级 JSON;你据此写出帮助用户快速判断长视频价值的报告。

Start Here

python scripts/bilibili_digest.py "<B站链接 / BV号 / AV号>"
  • 常用开关:--page N(分P,默认1)、--transcript full|head|none(字幕正文,默认full,超8000字自动截头部)、 --skip-comments--skip-uploader--no-cache
  • 无 CC 字幕时用 Whisper 兜底:python scripts/bilibili_whisper.py "<链接>" [--sample --peaks peaks.json] [--whisper-model small](需系统 ffmpeg)。
  • 脚本自带 24h 本地缓存(~/.cache/bilibili-summary/)与限速;stdout 是 UTF-8 JSON,进度走 stderr。

输出 JSON 契约(字段即事实源)

{
  "ok": true, "error": null,                 // ok=false 时仅含 error{code,message}
  "video": { "bvid","aid","title","desc","duration_sec","pubdate","tname","pages_total","current_page","url","tags" },
  "uploader": { "uid","name" },
  "uploader_profile": { "sign","official","followers","recent_videos":[{title,play,pubdate}] },  // 可能为 null
  "uploader_profile_error": null,            // 画像抓取失败时的原因串(区分"UP无数据"与"接口失败/wbi风控")
  "stats": { "view","like","coin","favorite","reply","danmaku","share" },
  "value_signals": { "like_rate","fav_rate","coin_rate","danmaku_per_min","reply_rate","hint" },
  "transcript": { "source":"subtitle|whisper|ai_conclusion_fallback|none", "subtitle_type":"cc|ai|null",
                  "text":"...", "truncated":false, "segments_sample":[{t,text}] },
  "auxiliary": { "ai_conclusion": { "available","source":"bilibili_official_ai","outline":[{title,timestamp}],"summary" } },
  "danmaku_analysis": { "total","top_words":[{word,count}],"density_buckets":[],"bucket_sec",
                        "peaks":[{t_sec,count,samples:[]}],"pbp_available" },
  "hot_comments": [{ "rpid","user","text","likes","reply_count","is_pinned","up_replied","sub_replies":[{user,text,likes}] }],
  "meta": { "fetched_at","cache_hit","requests_made","elapsed_sec" }
}

素材优先级transcript.source 标注本次内容来源。subtitle/whisper 是主内容源;ai_conclusion_fallback 仅在字幕与转写都拿不到时降级采用(B站自研小模型,质量低于你对全文的总结,用时必须注明来源)。 AI 小结永远只是 auxiliary 辅助信号(分段章节可作结构锚点)。

报告生成指令(决策导向)

依据 JSON 产出以下结构(无对应数据的小节注明"数据不足",不要编造):

一句话结论:值得完整看 / 看高能点即可 / 看本总结即可 / 不值得看(结合 value_signals 与内容判断)。 ② 内容摘要 + 分段大纲:基于 transcript.text(注明素材来源:字幕/转写/AI小结降级);有 auxiliary.ai_conclusion.outline 时用其时间戳作章节锚点。 ③ 高能点时间轴danmaku_analysis.peakst_sec + samples 代表弹幕 + 对应内容段落;pbp_available 为 true 时说明与官方高能进度条互相印证。 ④ 评论区共识与争议:对 hot_comments 做观点聚类;用 sub_replies(楼中楼)摘要争议交锋;区分"对内容的评价"与"对UP主的评价",输出共识观点、少数派观点、风评倾向。 ⑤ UP主风评(有 uploader_profile 时):画像(粉丝量、认证、近期作品)+ 本视频舆论倾向。 ⑥ 价值信号:列 value_signals 各互动率 + hint 判断依据。

错误处理指引

ok=false 时按 error.code 应对,不要重试到风控:

  • not_found:BV/AV 号可能有误或视频不可见,请用户核对。
  • auth:需要登录态(字幕/部分接口)——提示配置 cookies.jsonsessdata/bili_jct/buvid3);可继续用无需登录的字段。
  • rate_limited(-352/-412):触发风控,稍后再试,不要连续重试。
  • network:网络问题,检查连接后重试。
  • unknown:附原始 message 供排查。

配置与合规

  • Cookie 仅本地读取,优先 skill 目录 cookies.json,其次 ~/.hermes/skills/openclaw-imports/bilibili-summary/cookies.json不要泄露 SESSDATA/BILI_JCT
  • 保持脚本内置限速,不做任何绕过登录/风控的行为。
  • 依赖:pip install -e .(或 bilibili-api-python aiohttp);Whisper 兜底另需 pip install faster-whisper + 系统 ffmpeg。

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.