| name | blogify |
| description | Use this skill to turn a video or audio recording (a talk, meeting, or demo) into written content: documentation, a blog post, tutorial, changelog, or notes. Handles transcription, takeaway synthesis, screenshot/frame selection, and grounded drafting from local OpenAI-compatible media models. Not for real-time transcription, generic video editing, or non-generative media processing. |
| allowed-tools | Bash(uv run scripts/transcribe.py:*) Bash(uv run scripts/classify_frames.py:*) Bash(uv run scripts/sample_frames.py:*) Bash(uv run scripts/dedupe_frames.py:*) Bash(uv run scripts/extract_frame.py:*) Bash(uv run scripts/crop_frames.py:*) |
Blogify workflow
Produce four reviewable artifacts from the recording: transcript, takeaways,
selected frames, and final prose. Run the audio and frame tracks in parallel when
the input is video.
Requirements
$OMLX_BASE_URL must point at the OpenAI-compatible media endpoint (e.g.
http://127.0.0.1:14892); set $OMLX_API_KEY if it needs auth.uv (runs the bundled Python scripts and auto-installs declared
dependencies), ffmpeg, ffprobe, and ImageMagick (magick/convert) must
be available.- Keep all inputs and outputs in the user's workspace. Pass absolute paths; the
scripts refuse to write inside the skill directory.
First: get the intent
Collect the output type, audience, tone, and scope from the prompt or user
before drafting. Use references/authoring.md for the authoring checklist.
Workflow
- Transcribe. Run `uv run scripts/transcribe.py --input --output-dir
`. Produces `transcript.md` (timestamped) and `chunks.json`. The model is
auto-discovered (prefers parakeet); override with `--model`. For tuning and
limitations, use `references/transcription.md` (no timestamps, no diarization
— reconstruct/attribute accordingly).
- Mine takeaways. From the transcript, synthesize per-topic takeaways in
the reader's voice. Correct mistranscribed jargon against ground truth
(slides, repo names). Stay grounded — never invent claims. For long
recordings, fan out per-topic synthesis to sub-agents.
- Sample frames (in parallel with 1–2).
uv run scripts/sample_frames.py --input <video> --output-dir <sampled-frames-dir> grabs scene-change + periodic
frames named by timestamp. Then run uv run scripts/dedupe_frames.py --frames-dir <sampled-frames-dir> --output-dir <dedup-frames-dir> to drop
near-duplicates.
- Classify frames.
uv run scripts/classify_frames.py --frames-dir <dedup> --output <dir>/manifest.json --context "<one line about the video>" --categories "<A,B,...,OTHER>" --batch-size 4 --select-dir <selected-dir>. Use a SHORT enum of categories —
the vision model is a reliable classifier, a poor open-ended captioner. It
returns constrained JSON labels (validated against the enum). --batch-size
classifies several frames per request to amortize the endpoint's large fixed
per-request cost (~6–8 s); 4 is a safe default, raise it for distinct frames.
For sampling pitfalls, batching, and targeted re-sampling, use references/frames.md. The local OMLX
model is the default; if its per-request cost makes a large frame set
impractical even when batched, references/frames.md documents a privacy-gated cloud-subagent
fallback (only with explicit user consent, since frames leave the machine).
- Pick + polish images. For chosen frames, re-extract at full resolution
with `uv run scripts/extract_frame.py --input --second --output
/shot.png` and crop overlays with `uv run scripts/crop_frames.py`. Verify picks
visually before using them.
- Author the output. Draft the doc/blog per the requested intent. Add a
screenshot only where it makes the text easier to understand, placed next to
the concept, with descriptive alt text. Use
references/authoring.md.
- If in a repo, wire and validate. Follow the repo's image/LFS conventions,
optionally embed the recording/slides, run its markdown lint / link / TOC
checks, and respect its PR conventions (some repos want changes left in the
working tree). Use
references/authoring.md.
Notes
- Keep the transcript, takeaways, frame manifest, and selected frames in the
workspace — deliver the artifacts, not just the final prose.
- The transcript and the frame filenames share the video timeline, so you can
line up "demoed at 34:59" with the frame captured at 34:59.
- Run only the scripts bundled here; do not copy them elsewhere.
