# Video Review > Batch-review social video links (Instagram/Facebook/YouTube) against per-link free-text instructions. Fetches via Ollama Cloud Track A by default, falls back to real transcription+screenshots when a link's instruction needs exact claim verification or a timestamp. Claude verdicts every link, conditionally creates a Linear ticket, rolls everything into one consolidated report. - Skill: `abed-zahed/video-review` (Agent Skill, multi-file: 7 files) - Install (CLI): `npx skillmds@latest add abed-zahed/video-review` - Raw SKILL.md: https://api.skillmd.com/api/skills/abed-zahed/video-review/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: Abed-Zahed (https://skillmd.com/u/abed-zahed) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/abed-zahed/video-review --- # /video-review ## When to use The user gives you a batch of video links (Instagram, Facebook, YouTube), each paired with a free-text instruction, e.g.: ``` https://instagram.com/reel/abc123 - verify the claim they make about X, screenshot at 25s if true https://youtube.com/watch?v=xyz - just give me a digest, no ticket https://facebook.com/watch/def456 - if they're wrong about Y, make a JOB ticket ``` Links + instructions are pasted directly into the skill call. There is no queue file, every invocation is self-contained. ## Pipeline ### 1. Parse the batch Split the pasted input into `(link, instruction)` pairs. If a link has no instruction, treat it as "digest only, no ticket" (the safe default). ### 2. Route each link Read the instruction text yourself and classify it. This decision stays on Claude, it's a cheap read of a short string, not worth delegating. - **Needs real transcription** if the instruction asks to verify a specific claim precisely, quotes or paraphrases something exact that was said, or asks for a screenshot/frame at a timestamp. - **Digest only** otherwise, a general "what is this about", "summarize it", "is this worth my time" type instruction. ### 3. Check the Ollama Track A watcher (before any digest-only dispatch) Run: ```powershell Get-ScheduledTask -TaskName JobHunter_Ollama_DropfolderWatcher | Select-Object TaskName, State ``` - If `Running`, proceed. - If not, cycle it once: ```powershell Stop-ScheduledTask -TaskName JobHunter_Ollama_DropfolderWatcher -ErrorAction SilentlyContinue Start-ScheduledTask -TaskName JobHunter_Ollama_DropfolderWatcher ``` Re-check state. If still not `Running`, **stop and tell the user** the watcher is down and needs manual attention (registering a new task needs an interactive credential prompt only they can supply). Do not silently fall back to fetching every digest-only link yourself, that defeats the point of the delegation and burns tokens without saying so. Never invoke `run_ollama_batch.ps1` directly, self-invocation is blocked. Only the watcher process runs it. ### 4. Dispatch digest-only links to Track A For each digest-only link, write a task file to `D:\Projects\Agent_Orchestrator\ollama_dropfolder\tasks\.txt`: ``` glm-5.2:cloud Fetch and summarize this video link for a content-review batch: Give: what the video claims/covers, tone, and anything that looks like a factual claim worth double-checking. Plain ASCII only, no em dashes. ``` Poll `D:\Projects\Agent_Orchestrator\ollama_dropfolder\done\_done.txt` for the result (reasonable timeout, e.g. 3-5 minutes per link; these run sequentially through the watcher, a big batch takes longer, say so if it's running long). ### 5. Real transcription for links that need it For each verification-needed link: ``` py -3 D:\Projects\Shared_Content\video_transcriber\transcribe.py --model small --outdir --frames N ``` - Always `py -3`, never bare `python`/`python3` (Job Hunter's venv lacks yt-dlp/faster-whisper; the system `py -3` has them). - Use `--model small` for non-English audio, `tiny` can return empty transcripts on Arabic. - Before requesting a screenshot at a specific timestamp, check the video's actual duration first (transcribe.py reports it); a timestamp past the end will fail. If the instruction's requested timestamp is out of range, say so in the verdict rather than silently skipping it. - Convert any `/tmp/...`-style output path to a real Windows path before reading it with the Read tool. ### 6. Verdict (Claude only, never Ollama) For every link, compare what was fetched/transcribed against that link's own instruction and produce: - **Claim status**: verified true / verified false / unverifiable (say why) - **What the instruction asked for**: did you actually deliver it (screenshot taken, claim checked, etc.) - **One-line verdict summary** Sanity-check any tool/product name against known real names before calling a claim unverifiable. Whisper systematically mis-transcribes "Claude" as "Cloud" in tech-review content, if a transcript says "Cloud" in a context that's obviously about an AI assistant, treat it as "Claude" and verify accordingly. ### 7. Conditional Linear ticket Only create a ticket when the link's own instruction explicitly asks for one ("make a ticket if...", "log this", "ticket it"). Never invent ticket- worthiness yourself. Route by instruction content: - Mentions Job Hunter / CV / application context → Job Hunter, `JOB-`: ``` python -m src.linear_push --update TICKET-ID -d "..." ``` run from `D:\Projects\Job_hunter\`. - Mentions Azure / chocolates / business context → Azure, `SOLO-`: ``` python linear_push.py --update TICKET-ID -d "..." --project "Azure Projects" ``` run from `D:\Projects\Azure\Azure_projects\`. - If the instruction says to create a **new** ticket rather than update one, follow the same script's create path, still `--update`-style append semantics apply once it exists. **Never pass `--replace`.** ### 8. Output - **1-3 links total**: give every verdict directly in the chat response, no file written. - **More than 3 links**: build one consolidated report using `templates/report_template.html` (fill in one section per link: link, instruction, fetch method used, verdict, screenshot if any, ticket link if any), save to `reports/_batch_review.html` in the current project directory (create `reports/` if missing), then open it: ``` start reports/_batch_review.html ``` This is a plain local file, not a hosted Artifact. ## Known gotchas - Bash's bare `python` resolves to the wrong venv, always use `py -3` for video_transcriber calls. - `/tmp/...` paths need conversion to real Windows paths before Read can load them. - Whisper mis-transcribes "Claude" as "Cloud", sanity-check before flagging a claim unverifiable. - The watcher check is mandatory before every digest-only dispatch batch, not just the first link, it can go down mid-session.