Video to knowledge

SkillDocs & knowledge

Use by2kb to find videos for a learning topic, present numbered recommendations, and ingest the selected videos; also turn Bilibili/YouTube URLs or local media into transcripts, abstracts, and study notes.

Use Video to knowledge in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Video to knowledge and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the Video to knowledge skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Video to knowledgeStart free

What this skill tells your AI

The instructions your AI receives, as published by charlesmpc/by2kb in by2kb/integrations/hermes/skills/video-to-knowledge/SKILL.md and read by Ahel’s review.

The installed Hermes plugin handles a bare Bilibili or YouTube URL automatically. For a media attachment, first save the attachment to a private temporary path, then pass that exact path as the source argument. The workflow runs the deterministic transcription stage first, then uses the Hermes host model for bounded, program-planned enrichment operations. Do not clone or inspect the by2kb repository.

For an explicit/manual request:

  1. Check installation with by2kb version (0.5.3+). If missing or setup is incomplete, load the bundled skill_view("by2kb:install-by2kb"). The default installation is pipx install by2kb[asr-whisper,youtube] with by2kb init --preset agent-local.
  2. Use cloud Doubao ASR only when the user explicitly selects it. Never ask the user to send TOS or ASR credentials through an IM conversation.
  3. Run by2kb ingest <URL_OR_LOCAL_PATH> --enricher external_agent --json.
  4. Run by2kb enrichment next <JOB_ID> --provider <HOST_PROVIDER> --model <HOST_MODEL> --json.
  5. With by2kb 0.5.3+, needs_input returns a small operation ticket, not prompt text. Read both system_prompt and user_prompt using by2kb enrichment read --request-file <REQUEST_FILE> --field <FIELD> --offset 0 --limit 1000 --json. Continue using next_offset until eof for each field. Check every page's operation_id against the ticket. Follow the complete prompts, save the bounded response as UTF-8 (title operations request JSON, others Markdown), and run by2kb enrichment submit <JOB_ID> --operation-id <ID> --output-file <PATH> --provider <HOST_PROVIDER> --model <HOST_MODEL> --json.
  6. Repeat steps 4–5 until next returns status completed.
  7. Report the three knowledge-base paths: raw transcript, short abstract, and long-form study notes.

Never print an entire request file or transcript into terminal output. Do not chain claim and next; staged callers do not need claim. The program plans chunks and reductions; do not invent operation IDs or summarize unseen/truncated input. If a page is truncated, reread that offset with a smaller limit before continuing.

Inspect submit.status, not just its exit code. On operation_mismatch, query status and next, discard the old output, and generate for the new operation; stop after three resynchronizations. Never merely replace an ID on an old answer. On conflicting content or other errors, check job status and report the step issue without marking the shared job failed. Completed jobs should be reported as success. Never place model credentials in by2kb when using this path. Preserve checkpoints and user configuration. Older CLI inline prompts are compatibility-only; upgrade if its tool output is truncated.

Signals

GitHub stars
48
Forks
6
Last commit
Sep 2026
Advanced
Item type
skill
Key
video-to-knowledge
Source
github.com/charlesmpc/by2kb