# Codebase Video > Create a complete audience-targeted video explainer of the current codebase, combining verified screenshots, diagrams, animation, locally generated ComfyUI hero clips, narration and captions. Use for repository explainer videos, technical onboarding films and product walkthroughs; use the ComfyUI skill directly for a standalone generated clip. - Skill: `dreamlab-ai/codebase-video` (Agent Skill, multi-file: 7 files) - Install (CLI): `npx skillmds@latest add dreamlab-ai/codebase-video` - Raw SKILL.md: https://api.skillmd.com/api/skills/dreamlab-ai/codebase-video/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: dreamlab-ai (https://skillmd.com/u/dreamlab-ai) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dreamlab-ai/codebase-video --- # Codebase Video Produce an actual playable video and its editable production project from the repository in the current working directory. Tailor the story to the nominated audience. A storyboard, silent montage or unreviewed render is an intermediate artifact, not the completed request. Asking for **codebase video** invokes the complete process below by default. The user supplies the audience, relevant context and the final MP4 destination for that request, plus any explicit constraints. Source grounding, visual asset production, local generation, narration, captions, verification and the editable project are the skill's responsibility; they need no additional prompt wording. ## Ground the story Read the repository's instructions, entrypoints, README, relevant implementation and tests. Verify the running behaviour when describing a user flow. Record the repository revision and map each factual narration claim to a source file and, where useful, line ranges in `research.md`. Do not send private source files to external generation services. Prompts for local hero scenes should contain visual descriptions rather than repository contents. Use the user's audience, purpose and brand constraints. Let the material and the audience's needs determine the video's length, then derive scene timings from the narration. Honour an explicit duration constraint when supplied; otherwise there is no fixed runtime target. If the audience is absent, inspect context and ask one short question while gathering evidence. Explain user outcomes to buyers, concrete interactions to users, and interfaces/data flow/tradeoffs to engineers. Do not narrate a README's claims as tested behaviour. Create a project folder outside the source tree by default, or use the user's chosen output location. Keep `research.md`, `plan.json`, assets, narration, ComfyUI workflow JSON and runtime receipts together. Read [the manifest and production reference](references/production.md) before planning or composing. Read [seed design decisions](references/seed-design.md) only when extending the implementation or evaluating alternative renderers. Use the final MP4 destination specified for the current request. If it is missing, ask while progressing with research and production. After validation, copy the finished MP4 there and verify that its hash matches the project export. ## Produce the scenes Draft narration around one concrete problem, a demonstrated solution, an understandable mechanism and a useful next action. Plan a varied visual sequence: - Capture actual UI screenshots or interactions through the **browser** skill. Start the app using its documented command; use deterministic fixture data. For a library or CLI, capture a real invocation and output instead of inventing a web interface. Record the command or URL and the resulting asset. - Draw architecture/data-flow diagrams from source evidence. The bundled compositor provides a sequential diagram reveal; use **mermaid-diagrams** or code-native browser visuals for richer diagrams and frame-exact animations. Keep graph labels, code, captions, logos and exact UI text deterministic. For precise algorithms, queues, graph traversal or mathematical transformations, use [manim](../manim/SKILL.md) and its [video handoff](../manim/references/handoffs.md). Import its render as a video asset, retaining scene source and receipt beside it. - Generate cinematic metaphor/hero sequences locally with **comfyui**. Read its current video workflow reference, probe the sidecar and installed models, and follow the model download and smoke-test path before committing to a model. Save the API workflow, model identity, seed, prompt ID, history and downloaded output. Use the installed H3 profile by default after checking service/model compatibility; follow an explicitly requested model choice. Include at least one actual local model-generated hero by default unless the user opts out; a colour card or stock clip does not satisfy that requirement. Check current official model sources before calling a model state of the art. - Use **blender** when explanatory 3D geometry, camera moves or spatial mechanisms clarify the topic. Render a short deterministic clip or guide frames for ComfyUI; follow its video handoff reference. Coordinate GPU use: finish and unload the heavy model before a Blender render if VRAM is tight. Stage and unload models between phases as needed; use a second available GPU when necessary, following the ComfyUI device-selection reference. Preserve receipts and resume the same submitted job after an observation timeout. Generate narration **before locking durations**, using an available local TTS service or user recordings. The `scripts/narrate.py` helper calls the shared CPU Pocket service at `POCKET_TTS_URL` (default `http://pocket-tts:8000`), using background priority so interactive speech gets preference between segments. See the local narration recipe in the production reference. Measure every audio asset with `ffprobe`. Select an intelligible voice, listen for names/acronyms and correct pronunciation. Set each scene duration to cover its measured narration plus a short breathing interval. Do not substitute a tone or silent file for narration. Exact word highlighting requires real alignment timestamps; bundled captions use scene-level pacing. ## Compose and verify The deterministic helper needs Python 3, FFmpeg with libx264/drawtext and ffprobe. It uses the standard library and invokes subprocesses without a shell. Run it from the skill directory, using absolute paths for the production project: ```bash python3 scripts/video_project.py validate /absolute/project/plan.json python3 scripts/video_project.py compose /absolute/project/plan.json \ --output /absolute/project/delivery-v1 ``` Use `--preview` only for explicitly labelled drafts without narration. A delivery folder must be new; iteration creates `delivery-v2` rather than overwriting the previous review. Import richer Remotion/Videowright/Blender/Manim exports as video scenes rather than stretching the bundled simple compositor beyond its purpose. Open the final MP4, inspect representative frames from **every scene**, play the narration and all cuts, and correct clipping, unreadable text, bad pronunciation, unsupported claims or visual artifacts. Verify total runtime, video dimensions, audio and caption streams. Review the MP4's embedded selectable subtitles and sidecar SRT; burn them into an additional export if the destination needs that. Generated clips must have stable subjects, intentional movement and no stray text. Screenshots must remain readable at the delivery size. Record this human or agent editorial inspection in `review.md`; the automated receipt deliberately says `rendered-needs-editorial-review` and cannot prove these qualities. Deliver `explainer.mp4`, `poster.jpg`, `captions.srt`, `transcript.md`, `plan.json`, `receipt.json` and the production project with source assets/workflows. Explain any unresolved limitation accurately. Completion requires the audience's central question to be answered by the rendered and reviewed video, not merely green manifest validation. Publishing is a separate action and needs user authority. ## Related skills - `explainer` — the family hub for codebase explainers. When its video delivery hands off here, it passes the audience and a claims ledger (`claim → file:line`) already gathered from its own orientation pass; this skill still independently re-verifies runtime behaviour rather than accepting a claim on trust. - `open-montage` — use it instead for video with no codebase grounding: a trailer, an avatar spokesperson, a podcast repurpose, or any request not targeting the current repository.