Video Deep Reader

--- name: video-digest version: 2.0.6 description: 把一段视频变成能读的笔记——公开字幕抓进本地私有缓存，按时间戳产出 Quick / Deep / Research 三档笔记，每句都能定位回原片。适合"三十分钟的视频只想花三分钟"和"口播内容想存成可检索文字"。Turn a video into timestamped Quick / Deep / Research notes from public captions or a supplied transcript, cached privately per user. Use when the user shares a video link and wants a summary, deep notes, or a citation-ready excerpt; also when they ask whether captions are available or why transcript fetching fails. allowed-tools: RunCommand, Bash, Read, Write, WebSearch, WebFetch metadata: openclaw: requires: bins: [python3] --- # Video Deep Reader ## What It Does Turn a YouTube video or supplied transcript into a useful reading artifact: - **Quick**: decide in a minute whether the video is worth watching. - **Deep**: understand the argument, evidence, structure, and important timestamps. - **Research**: verify selected material claims against public primary sources. The bundled fetch helper retrieves public metadata and subtitles; Research mode may additionally verify selected claims with public sources. The agent creates the semantic notes from these inputs. Bundled components are deliberately separate: - `fetch_video.py --doctor` checks the local dependency and optional network readiness. - `fetch_video.py` retrieves public metadata and subtitles into the declared temporary cache. - `fetch_video.py --retrieve-video` returns timestamped excerpts from that cache by validated video ID. - The agent applies this file and `references/output-modes.md` to create the semantic notes. ## When to Use Invoke when the user: - provides a YouTube URL or video ID and asks to summarize, analyze, or understand it; - pastes or uploads a transcript and asks for video notes; - asks a follow-up question about a previously fetched video; - wants to compare several videos or decide which one deserves deeper attention; - asks to verify important claims made in a video. A bare YouTube URL is enough only when the message is clearly asking the assistant to process that video. Do not activate when a link is merely cited, shared as a reference, requested for playback or download, or included as one source inside an unrelated task. Do not invoke for: - downloading the video or audio; - bypassing login, age, geographic, paywall, or access controls; - summarizing a video that has neither accessible subtitles nor a user-supplied transcript; - publishing derived content without an explicit request. ## Output Language Respond in the language of the user's current request. If unclear, ask once. Preserve quotations in their original language and add a translation only when useful. Bundled scripts emit machine-readable JSON, status codes, and transcript text rather than a localized natural-language interface. Explain their results in the language of the user's current request. ## Select the Mode | Request signal | Mode | Default output | |---|---|---| | Bare link, “总结”, “讲了什么”, “值不值得看” | Quick | One-screen decision card | | “深读”, “完整笔记”, “论证过程”, “详细整理” | Deep | Timestamped structured notes | | “核验”, “查证”, “research”, “是真的吗” | Research | Deep notes plus selected claim verification | | Two or more links | Batch Quick | One Quick card per video | If the requested depth is ambiguous, use Quick as the content mode. Still follow host confirmation requirements for package installation, file creation, and every other state-changing action. ## Step 1: Check the Environment Run the read-only doctor before the first URL fetch in a session: ```bash python3 <skill_dir>/scripts/fetch_video.py --doctor ``` Add `--network` only when a network diagnosis is needed. If a local proxy should be tested, pass its loopback port explicitly with `--proxy-port`; Doctor does not scan local ports. Doctor never installs packages or changes configuration. If the pinned dependency is missing, show the exact repair command: ```bash python3 -m venv .venv .venv/bin/python -m pip install --require-hashes -r <skill_dir>/requirements.lock ``` Do not install anything without explicit user approval. ## Step 2: Get a Transcript ### YouTube URL or video ID Run: ```bash python3 <skill_dir>/scripts/fetch_video.py "<youtube-url>" ``` For a local proxy, pass only the loopback port: ```bash python3 <skill_dir>/scripts/fetch_video.py "<youtube-url>" --proxy-port 7890 ``` The script: - validates YouTube hosts and video IDs; - calls the pinned `yt-dlp` Python API directly; - never invokes a shell or external executable; - accepts only a loopback proxy port and no proxy credentials; - writes `meta.json` and `transcript.txt` to a private per-user cache under the system temporary directory; - prints the cache directory as JSON. The cache hierarchy must be owned by the current user with `0700` directory permissions. Cache files use atomic replacement, `0600` permissions, and reject symbolic links. Temporary cache is not a durable archive. Create a user-visible note file only when the user explicitly requests one. ### Supplied transcript If the user provides transcript text or a transcript file, skip YouTube fetching. Treat it as `User-provided transcript` and preserve any timestamps already present. ### No subtitles or failed fetch Do not stop at “unsupported.” Offer the smallest viable fallback: 1. Ask the user to paste or upload a transcript. 2. If the user already supplied an audio/video file, use an available transcription capability only with the user's request. 3. If neither is available, explain the exact limitation without inventing content. ## Step 3: Produce the Requested Output Follow `references/output-modes.md`. ### Quick Keep it to one screen: - title, channel, duration, and source link; - 2–3 sentence summary; - five timestamped takeaways; - one “worth watching if…” judgment; - important uncertainty or missing context. ### Deep Include: - concise overview; - timestamped structure; - argument map: claim → reasoning → evidence → limitation; - `Video statement` and `Author opinion` as separate labels; - notable quotations; - unanswered questions and useful follow-ups. Do not call a statement a verified fact merely because it appears in the video. ### Research Start from Deep, then verify only material claims that affect the conclusion. - Prefer primary sources, official documentation, papers, or original datasets. - Attach each verification result to the corresponding video timestamp. - Label each claim `Supported`, `Partly supported`, `Contradicted`, or `Not verified`. - State source date and scope. - Do not perform broad web research when the user only asked for a summary. ### Batch Quick For each video provide: - one-sentence thesis; - three key timestamps; - evidence quality; - novelty; - recommendation: Deep now / Save / Skip. Compare videos only on common dimensions. ## Follow-up Retrieval The retrieval script accepts a video ID, never an arbitrary file path: ```bash python3 <skill_dir>/scripts/fetch_video.py --retrieve-video <video-id> --keyword "attention" python3 <skill_dir>/scripts/fetch_video.py --retrieve-video <video-id> --at 3:20 python3 <skill_dir>/scripts/fetch_video.py --retrieve-video <video-id> --list ``` It reads only transcripts created under the managed temporary cache. Quote the relevant timestamp range in the answer. ## Content Integrity - Preserve what the source actually says; remove filler, not substance. - Separate a video's claims from external verification. - Keep numbers, dates, named entities, caveats, and uncertainty. - Trust visible slide text over an obvious transcription error when the user supplies frames or screenshots. - Do not attribute a claim to a speaker unless the source supports the attribution. - Do not turn the summary into promotional copy unless explicitly requested. ## Completion Standard - The selected mode matches the request. - Every major point can be traced to a timestamp or labeled transcript section. - Claims and opinions remain separate. - Research mode includes source-backed verification and scope. - Fetch failures produce a usable transcript fallback. - No package installation, durable file write, publishing, or external state change occurs without explicit approval.

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