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Bilibili Page Reader

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Misaka-Mikoto-Tech
bilibili-page-reader

Get content from Bilibili videos: official subtitles, danmaku (density/peaks/sample), comments. When no subtitles exist (no 投稿字幕), fall back to downloading audio + ASR transcription via FunASR.

Overview

PublisherMisaka-Mikoto-Tech
Repositoryagent-skills
Skill namebilibili-page-reader
Stars
283
Forks
11
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Misaka-Mikoto-Tech on GitHub. Read the source before you install it.

Installation

Install the Bilibili Page Reader AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Misaka-Mikoto-Tech/agent-skills/tree/main/skills/bilibili-page-reader
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Misaka-Mikoto-Tech/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/bilibili-page-reader .claude/skills/bilibili-page-reader
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bilibili Page Reader in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bilibili Page Reader on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bilibili Page Reader is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bilibili Page Reader

Core Rules

  • Browser access via kimi-webbridge for page state, login-only data, Bilibili Evolved (BE) providers.
  • Do not click BE download buttons. Call providers directly via evaluate.
  • Always use a named session. A session-less evaluate may land on a different tab and silently return wrong data.
  • Network calls outside the browser (audio download, playurl API) use Node.js — PowerShell's curl.exe and Python's requests both get blocked by Bilibili CDN TLS fingerprinting on this platform.

Workflow Overview

                    ┌─ BE downloadSubtitles provider ──→ 投稿字幕 (timestamps)
                    │
BiliBili video ───┼─ BE downloadDanmaku provider ────→ danmaku density/peaks/sample
                    │
                    └─ No subtitles? ──→ Audio transcription fallback
                                         1. Get audio stream URL (Node.js → playurl API)
                                         2. Download .m4s audio
                                         3. ffmpeg → .m4a
                                         4. FunASR paraformer-zh → SRT with timestamps

Phase 1: Subtitles (preferred — via BE)

Use the one-shot evaluate below. It returns both subtitles and danmaku in a single call.

Setup

bash
~/.kimi-webbridge/bin/kimi-webbridge status
json
{"action":"navigate","args":{"url":"https://www.bilibili.com/video/BV.../","newTab":true},"session":"bilibili"}

Wait 2–3 seconds for BE to fully initialize.

One-shot evaluate

js
(async () => {
  const pa = window.bilibiliEvolved.pluginApis;

  // ── Identifiers ──
  const s = window.__INITIAL_STATE__ || {};
  const vd = s.videoData || {};
  const bvid = vd.bvid || s.bvid || location.pathname.match(/BV[\w]+/)?.[0];
  const aid = vd.aid || s.aid;
  const pages = vd.pages || [];
  const p = parseInt(new URLSearchParams(location.search).get('p') || '1') - 1;
  const cid = pages[p]?.cid || vd.cid || s.cid || pages[0]?.cid;
  const title = vd.title || document.title;

  // ── Register providers ──
  pa.registerData('downloadVideo.assets', []);

  // ── Poll for providers (downloadDanmaku loads async, ~1-2s) ──
  function getProviders() {
    const g = pa.getData('downloadVideo.assets');
    return Array.isArray(g[0]) ? g.flat() : g;
  }
  const deadline = Date.now() + 5000;
  let providers = getProviders();
  while (!providers.find(p => p.name === 'downloadDanmaku') && Date.now() < deadline) {
    await new Promise(r => setTimeout(r, 300));
    providers = getProviders();
  }

  // ── Subtitles: try 投稿字幕 first ──
  let subResult = { count: 0, text: '', source: 'none' };
  const subProvider = providers.find(p => p.name === 'downloadSubtitles');
  if (subProvider) {
    try {
      const subAssets = await subProvider.getAssets([{ input: {} }], { type: 'json', enabled: true });
      const subRaw = subAssets[0].data;
      let subText;
      if (subRaw instanceof Blob) {
        const buf = await subRaw.arrayBuffer();
        subText = new TextDecoder('utf-8').decode(buf);
      } else {
        subText = String(subRaw);
      }
      const subtitles = JSON.parse(subText);
      const subLines = subtitles.map(s => {
        const totalSec = Math.floor(s.from);
        const h = Math.floor(totalSec / 3600);
        const m = Math.floor((totalSec % 3600) / 60);
        const sec = String(totalSec % 60).padStart(2, '0');
        if (h > 0) {
          return '[' + h + ':' + String(m).padStart(2, '0') + ':' + sec + '] ' + s.content;
        }
        return '[' + m + ':' + sec + '] ' + s.content;
      });
      subResult = { count: subtitles.length, text: subLines.join('\n'), source: '投稿字幕' };
    } catch(e) {
      subResult = { count: 0, text: '', source: '投稿字幕_error' };
    }
  }

  // ── Danmaku: analyze in-page, summary only ──
  const dmk = providers.find(p => p.name === 'downloadDanmaku');
  const dmkAssets = await dmk.getAssets(
    [{ input: { aid: String(aid), cid: String(cid) } }],
    { type: 'json', enabled: true }
  );
  const dmkRaw = dmkAssets[0].data;
  let dmkText;
  if (dmkRaw instanceof Blob) {
    const buf = await dmkRaw.arrayBuffer();
    dmkText = new TextDecoder('utf-8').decode(buf);
  } else {
    dmkText = String(dmkRaw);
  }
  const danmaku = JSON.parse(dmkText);

  // Time density: 30s buckets
  const bucketSize = 30;
  const buckets = {};
  for (const d of danmaku) {
    const b = Math.floor(d.progress / 1000 / bucketSize) * bucketSize;
    buckets[b] = (buckets[b] || 0) + 1;
  }
  const density = Object.entries(buckets)
    .map(([t, c]) => [Number(t), c])
    .sort((a, b) => a[0] - b[0]);

  // Top 5 peak moments
  const peaks = density.slice().sort((a, b) => b[1] - a[1]).slice(0, 5);

  // Stratified sample: up to 40 entries across full timeline
  const sampleCount = Math.min(40, danmaku.length);
  const step = Math.max(1, Math.floor(danmaku.length / sampleCount));
  const danmakuSample = [];
  for (let i = 0; i < danmaku.length && danmakuSample.length < sampleCount; i += step) {
    danmakuSample.push({
      t: Math.floor(danmaku[i].progress / 1000),
      c: danmaku[i].content
    });
  }

  const totalDuration = danmaku.length > 0
    ? Math.max(...danmaku.map(d => d.progress)) : 0;

  // ── Return ──
  return JSON.stringify({
    ok: true, bvid, aid: Number(aid), cid: Number(cid), p: p + 1, title,
    sub: subResult,
    dmk: {
      count: danmaku.length,
      timeSpanSec: Math.floor(totalDuration / 1000),
      density,
      peakMoments: peaks.map(pk => ({ timeSec: pk[0], count: pk[1] })),
      sample: danmakuSample
    }
  });
})()

Response shape

json
{
  "sub": {
    "count": 243,
    "text": "[0:00] 大家好\n[0:01] 这个视频...",
    "source": "投稿字幕"
  },
  "dmk": {
    "count": 247,
    "density": [[0,11], [30,2], ...],
    "peakMoments": [{"timeSec": 1170, "count": 16}, ...],
    "sample": [{"t": 0, "c": "辛苦惹!"}, ...]
  }
}

If sub.count === 0, no 投稿字幕 was available. Proceed to Phase 2 below.


Phase 2: Audio Transcription Fallback (when no subtitles exist)

Use when Phase 1 returns sub.count === 0. This replaces the old "AI subtitle API" fallback which is unreliable — the /x/player/v2 API often returns stale/empty subtitle data.

Why this approach

The Bilibili CDN uses TLS fingerprinting that blocks curl and Python requests. Reliable paths:

MethodWorks?Notes
curl.exe with browser headers❌ Exit code 35SSL blocked
Python requests / urllib❌ BlockedSame reason
Node.js https.get()✅Use User-Agent + Referer headers
Browser fetch (in-page)✅ but evaluate timeout <1sOnly for fast API calls
Node.js to download audio✅Backup URL is most stable

Step 1: Get audio stream URL via Node.js

bash
node -e "
const https = require('https');
const url = 'https://api.bilibili.com/x/player/playurl' +
  '?bvid=BVxxxxxxxxx&cid=xxxxxxxxx&qn=0&fnval=4048&fourk=1&platform=web';
https.get(url, {
  headers: {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
    'Referer': 'https://www.bilibili.com/'
  }
}, (res) => {
  let data = '';
  res.on('data', (chunk) => { data += chunk; });
  res.on('end', () => {
    const d = JSON.parse(data);
    if (d.code === 0 && d.data && d.data.dash && d.data.dash.audio) {
      const audio = d.data.dash.audio;
      const best = audio.reduce((a,b) => a.bandwidth > b.bandwidth ? a : b);
      console.log(best.baseUrl + '|' + (best.backupUrl ? best.backupUrl[0] || '' : ''));
    } else {
      console.log('ERROR: no dash audio data');
    }
  });
}).on('error', (e) => { console.log('ERROR: ' + e.message); });
"

The fnval=4048 flag requests DASH format with separate audio/video streams.

Step 2: Download audio (use backup URL — most reliable)

bash
node -e "
const https = require('https');
const fs = require('fs');
const url = 'BACKUP_URL_FROM_STEP_1';
const file = fs.createWriteStream('output.m4s');
https.get(url, {
  headers: {
    'User-Agent': 'Mozilla/5.0 ...',
    'Referer': 'https://www.bilibili.com/'
  },
  timeout: 60000
}, (res) => {
  if (res.statusCode !== 200) { console.log('HTTP ' + res.statusCode); return; }
  res.pipe(file);
  res.on('end', () => { console.log('OK size=' + file.bytesWritten); });
}).on('error', (e) => { console.log('ERR: ' + e.message); });
"

Step 3: Convert to standard audio (stream copy, no re-encode)

bash
ffmpeg -i output.m4s -c copy output.m4a -y

Step 4: ASR transcription via FunASR

bash
set MODELSCOPE_CACHE=.\cache\modelscope
set MODELSCOPE_CREDENTIAL_PATH=.\cache\modelscope_cred
python audio2srt.py output.m4a --srt --model paraformer-zh --punc-model ct-punc --spk-model cam++

Step 5: Cleanup — remove intermediate audio files

bash
del output.m4s output.m4a

The only artifacts worth keeping are the .srt subtitle file. The raw .m4s, the converted .m4a, and any .json debug output are all intermediate and should be cleaned up after the SRT is confirmed valid.

What the script does:

  • Loads paraformer-zh (Chinese ASR, 220M params) + fsmn-vad + ct-punc + cam++
  • Outputs SRT with per-sentence timestamps via res[0]["sentence_info"]
  • CPU perf: ~15x realtime (21 min audio ≈ 90 sec)
  • Handles ModelScope cache/credential path setup automatically

If cam++ is too slow to download, omit --spk-model and group res[0]["timestamp"] (per-character ms array) by punctuation boundaries manually.

If no sentence_info in the output: the spk_model triggers sentence segmentation. Without it, you only get raw text + per-character timestamps.

The audio2srt.py script

Located next to this SKILL.md file. Copy it into the current workspace or call it by its skill-directory path. It handles:

  • Model loading with ModelScope credential path override (sandbox-safe)
  • Multiple output formats: SRT, VTT, JSON
  • Parsing sentence_info, timestamp, and raw text fallback
  • Cleaning SenseVoice special tags (<|zh|>, <|HAPPY|>, etc.)
  • Segment deduplication and time-sorting

After transcription completes, delete *.m4s and *.m4a — only the .srt is the final output.


Danmaku Fallback: Protobuf API (when BE's downloadDanmaku is absent)

js
(async () => {
  const be = window.bilibiliEvolved;
  const proto = await be.runtimeLibrary.protobufLibrary;

  const schema = {
    nested: {
      DmSegMobileReply: {
        fields: { elems: { rule: 'repeated', type: 'DanmakuElem', id: 1 } },
      },
      DanmakuElem: {
        fields: {
          id: { type: 'int64', id: 1 },
          progress: { type: 'int32', id: 2 },
          mode: { type: 'int32', id: 3 },
          fontsize: { type: 'int32', id: 4 },
          color: { type: 'uint32', id: 5 },
          midHash: { type: 'string', id: 6 },
          content: { type: 'string', id: 7 },
          ctime: { type: 'int64', id: 8 },
          pool: { type: 'int32', id: 11 },
          idStr: { type: 'string', id: 12 },
          attr: { type: 'int32', id: 13 },
          animation: { type: 'string', id: 22 },
        },
      },
    },
  };
  const root = proto.Root.fromJSON(schema);
  const DmSegMobileReply = root.lookupType('DmSegMobileReply');

  const raw = await new Promise((resolve, reject) => {
    be.monkeyApis.GM_xmlhttpRequest({
      method: 'GET',
      url: `https://api.bilibili.com/x/v2/dm/web/seg.so?type=1&oid=${cid}&pid=${aid}&segment_index=1`,
      headers: { 'Referer': 'https://www.bilibili.com/' },
      responseType: 'arraybuffer',
      onload: r => resolve(r.response),
      onerror: r => reject(r.responseType)
    });
  });
  const decoded = DmSegMobileReply.decode(new Uint8Array(raw));
  return JSON.stringify(decoded.elems || []);
})()

If segment 1 has data and segment 2 is empty, treat segment 1 as complete. Apply the same density/peak/sample logic from Phase 1.


Comments

text
https://api.bilibili.com/x/v2/reply/main?jsonp=jsonp&type=1&oid={aid}&mode={mode}&ps=20&next=0

Modes: 2 = newest, 3 = popular, 0 = popular (server-dependent). Use DOM to confirm render order.


Data Structures

投稿字幕 (from BE downloadSubtitles)

js
[
  { "from": 0.3, "to": 5.3, "sid": 1, "location": 2, "content": "文字内容", "music": 0 },
  ...
]

Danmaku

js
{ "progress": 40000, "mode": 1, "fontsize": 25, "color": 16777215,
  "content": "弹幕内容", ... }

progress is in milliseconds.

DASH audio stream (from playurl API)

  • fnval=4048 → DASH response with dash.audio[]
  • Audio IDs: 30216 (~65kbps), 30232 (~74kbps), 30280 (~128kbps AAC)
  • Codec: mp4a.40.2 (AAC-LC, 48kHz, stereo)
  • Format: .m4s = fragmented MP4, valid for ffmpeg stream copy

ASR output (sentence_info)

js
[
  { "start": 110, "end": 2190, "text": "话说大家有没有见过那种反驳型人格", "spk": 0 },
  { "start": 2330, "end": 3750, "text": "就是不管听到你说什么,", "spk": 0 },
  ...
]

start/end in milliseconds. spk is the speaker ID (from cam++ diarization).


Gotchas

IssueWhat to do
downloadDanmaku not in providersPolling loop handles this. If absent after 5s, fall back to Protobuf API.
Session-less evaluateAlways use "session":"bilibili" or similar.
registerData() without []Always pass []. Provider callbacks crash without data.
Blob.text() hangsUse arrayBuffer() + TextDecoder('utf-8').decode() instead.
CDN blocks curl.exeUse Node.js https.get() with browser UA + Referer.
playurl API returns no dashDon't use platform=html5. Use fnval=4048&platform=web.
Audio URL returns 403URLs expire after ~5 min (deadline param). Fetch + download immediately in one pass.
ModelScope cache permission deniedSet MODELSCOPE_CACHE + MODELSCOPE_CREDENTIAL_PATH to writable workspace dirs. The audio2srt.py script handles this.
No sentence_info in outputAdd --spk-model cam++ to trigger sentence segmentation.
Nested array from getDataAlways flatten: Array.isArray(g[0]) ? g.flat() : g.
curl.exe downloadingUse node -e with https.get() instead.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bilibili Page Reader AI skill do?

Get content from Bilibili videos: official subtitles, danmaku (density/peaks/sample), comments. When no subtitles exist (no 投稿字幕), fall back to downloading audio + ASR transcription via FunASR.

Why use Bilibili Page Reader on TypingMind?

Because you install it once and use it with any model. Bilibili Page Reader is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bilibili Page Reader in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Misaka-Mikoto-Tech/agent-skills/tree/main/skills/bilibili-page-reader. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bilibili Page Reader?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bilibili Page Reader?

As many as you like. As long as a model supports skills, you can use Bilibili Page Reader with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bilibili Page Reader AI skill free?

Yes. It is published on GitHub by Misaka-Mikoto-Tech under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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