Short Publish

Overview

This skill automates the complete "video → subtitles → PostFlow" pipeline: run Whisper-based transcription, burn subtitles with the bundled Python script, turn the transcript into a multi-platform copy block, and schedule social posts through the PostFlow CLI.

Inputs & Prerequisites

• Arguments:

- PATH – absolute path to the source video (MOV/MP4/etc.). - DATETIME – publication date/time (accepts natural language like "tomorrow 09:00"). Use date to confirm the current timestamp if needed.

• Tooling: use the postflow CLI (postflow media upload, postflow posts create) and refer to [postflow-cli](../postflow-cli/SKILL.md) for command details.
• Script dependency: scripts/transcribe_burn.py wraps Whisper, ffmpeg, and auto-gain. Requires Python 3.8+, ffmpeg, and openai-whisper installed for the user; no extra configuration is needed inside this skill.
• Timezone: default to Europe/Madrid. In winter assume UTC+01:00 (CET) when presenting final schedules if the date command does not provide the offset.

Workflow

1. Collect inputs

- Confirm the provided PATH exists; stop with a descriptive error if not. - Resolve DATETIME to an ISO timestamp. Use date -j -f or another deterministic macOS command when the input is natural language so PostFlow receives an unambiguous value.

1. Transcribe and burn subtitles

- Run the bundled helper: python3 scripts/transcribeburn.py "$PATH". - Outputs (all written next to the original video): - <stem>.srt, <stem>.ass, <stem>.txt, <stem>caption.txt, <stem>subtitled.mp4. - The subtitled.mp4 is the media you will upload; everything else is transient reference material. Remove the generated artifacts (srt/ass/txt/caption/mp4_subtitled/normalized wav) once they have been read and the upload succeeds—never delete the original video.

1. Generate the social copy

- Read <stem>.txt for the full transcript. - Apply the exact copywriting prompt below to the transcript; do not improvise structure or tone beyond the template.

``` Act as an expert LinkedIn copywriter building authority content. Transform the TRANSCRIPT into a case-study or practical-lesson post with this structure: 1. Hook headline with a leading emoji. 2. 2-3 sentence context introducing the situation. 3. Structured core (use 1️⃣/2️⃣/3️⃣ or ✅ and bold keywords per line). 4. Closing takeaway line. 5. Optional P.S. only when the transcript mentions an offer/event.

Style rules: short paragraphs (1-2 lines), intentional emoji usage, no invented facts, stay faithful to the transcript. ```

- Reuse the single output block verbatim for LinkedIn, X, and Instagram, and as the YouTube description (light line breaks allowed). Craft a YouTube title ≤100 characters from the same content.

1. Upload the subtitled video

- Upload the subtitled.mp4 and capture mediaid: ``bash postflow --json media upload --file "<stem>subtitled.mp4" --kind video ` - Use the returned id as mediaid` for all posts.

1. Schedule posts via postflow posts create

- Accounts come from ~/.config/skills/config.json under postflow.groups.shortpublish and postflow.accounts. - For X aliases, use postflow.defaults.x (default x-es) unless the user explicitly requests another account. - For each account, create a scheduled post with the same copy block and the uploaded media: ``bash postflow posts create \ --account-id <accid> \ --text "<copyblock>" \ --media-id <mediaid> \ --scheduled-at <ISO8601> ` - If a thread is needed, use --segments-json instead of --text`.

1. Report completion

- Confirm each scheduled post by echoing returned IDs and scheduled time in CET (UTC+01:00 during winter). Example: LinkedIn pst_... → 2025-01-11T10:00:00+01:00 (CET).

Resources

• scripts/transcribe_burn.py: Whisper + ffmpeg pipeline used in Step 2. Copy-safe to reuse elsewhere but do not edit unless the video workflow changes. Running the script produces all intermediate assets and the burned MP4 referenced throughout the workflow.