/socialforge:generate-video — Video Production Kit

Script location. If your host does not set ${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin's scripts/ folder, next to skills/. Run them with Python 3.10 or newer: python, or python3 where python is not found (macOS, many Linux systems).

Generate video production assets through a 5-stage human-in-the-loop pipeline. Each stage requires user approval before advancing.

Context efficiency

Asset-heavy skill. Grep before Read the asset catalog (${CLAUDE_PLUGIN_DATA}/socialforge/brands/<brand>/asset-index.json) — never list the asset directory. Reference generated images / videos by path, not by loading metadata. Brand profile loads once per session.

Prerequisites

• Credentials must be configured via /socialforge:setup:
• Vertex AI (registry alias latest-image-google) — used for first-frame and last-frame keyframe generation
• WaveSpeed API (registry alias latest-video-wavespeed) — used for image-to-video generation
• Models are never named in this skill: each alias above is resolved to a current model id when the script runs. To see what they resolve to today, run python "${CLAUDE_PLUGIN_ROOT}/scripts/generate_video.py" --list-models (video) or python "${CLAUDE_PLUGIN_ROOT}/scripts/resolve_model.py" --aliases (every alias).
• Brand profile must be active (/socialforge:switch-brand if needed)
• Calendar must be parsed (/socialforge:parse-calendar) with video posts identified

Quote, then go (before any paid call)

Generation spends provider credits, so the first paid call waits for a quote and an explicit go. This skill states no price and the model registry stores none: price_book.py is the only source, and it refuses rather than guesses.

1. List what is about to be generated: for each paid call, the registry alias (resolve_model.py --alias <alias> gives the current model id), the provider, and the units (images, or seconds of video, plus any option that changes the price, such as synchronised audio). The first paid call is Stage 2, so quote the whole chain (the keyframes of Stages 2 and 3 and the clip of Stage 4) once, before Stage 2.
2. Quote it:

python "${CLAUDE_PLUGIN_ROOT}/scripts/price_book.py" --action quote-batch --items '[{"model":"<resolved model id>","provider":"<provider>","units":<n>,"label":"<post id and stage>"}]'

A single item can use --action quote --model <id> --provider <provider> --units <n>. If the quote exits non-zero or lists a blocked item, stop: run /socialforge:price-check to look the missing price up, then quote again.

1. Show the user the total, each line, its source URL, and how old the price is (a price older than 24 hours is stale and is refused; it must be looked up again):

Estimated cost: <total_usd> USD for <n> generations. Prices from <source>, <age_hours> h old (valid for 24 h).
Type "go" to generate. Anything else cancels.

1. Continue only on an explicit go for exactly this list. Anything else, including silence, cancels and nothing is generated. If the list changes (more posts, another model, an added option), quote again and ask again. A quote is never approval (approved_to_run is always false).

The 5-Stage Pipeline

Stage 1: Video Concept + Script (no API call)

Claude generates 2-3 video concept ideas based on the post brief, brand voice, and platform requirements. Each concept includes:

• Working title and hook
• Visual narrative arc (opening, middle, close)
• Suggested duration and pacing
• Tone and style direction

The user picks one concept (or requests refinements). Then fill the script scaffold (generate_script in generate_video.py) from the chosen concept and the post's actual brief, in the brand's voice — every [FILL] replaced, no placeholder survives into Stage 2. The scaffold enforces the structure; this pass supplies the craft, under four rules the scaffold carries with it:

1. Hook first, never the logo. The open earns attention with the single

most arresting thing the brief supports; the brand mark lives as the corner watermark and in the end card. Three seconds of logo reveal is the classic retention killer this pipeline used to scaffold by default.

1. Payoff per scene. Every scene's payoff field states what the viewer

has gained by the time it ends. A beat that only sets up the next beat is where viewers leave — give it a payoff or fold it.

1. The pairing rule. The hook's text overlay and the post's caption

(written by adapt-copy) do different jobs and never echo. Check against the adapted copy if it already exists for this post.

1. Compliance before credits. Run the filled script's narration and

overlay text through compliance_check.py BEFORE Stage 2 — a banned phrase caught in a script costs nothing; caught in a rendered video it costs the whole generation chain. Claims in narration follow the same rules as claims in copy: sourced or absent.

The user approves the filled script before any generation spend.

Stage 2: First Frame Generation (Vertex AI, latest-image-google)

First: Quote, then go (the section above). Nothing is generated until the user types go.

Generate 2 first-frame options based on the chosen concept. These set the opening visual and establish the look and feel.

• Images are shown inline in the terminal for immediate review
• User selects one or requests a regeneration with adjusted direction

Stage 3: Last Frame Generation (Vertex AI, latest-image-google)

Generate 2 last-frame options that complete the visual narrative arc, matching the approved first frame.

• Images are shown inline in the terminal for immediate review
• User selects one or requests a regeneration with adjusted direction

Stage 4: Video Generation (WaveSpeed, latest-video-wavespeed)

Using the approved first and last frames, generate 2 video versions through generate_video.py --generate-video --image <first-frame> --last-image <last-frame> (the WaveSpeed image-to-video endpoint, 3-15 seconds). The first frame goes to every provider in the chain; the last frame goes to the kling rung only, as the clip's end image. After each run, read video.last_frame_used before presenting a clip as landing on the approved last frame — see "Keyframe and reference inputs" below.

• A video gallery is opened in the browser for side-by-side comparison
• User selects the final version or requests a regeneration

Stage 5: Post-Process, Save & Deliver

After the user picks the final video, post-processing runs before saving:

• Logo watermark is automatically added to the video via video_postprocess.py
• Subtitles: User is asked whether to burn subtitles into the video (optional). SRT was already generated from the script and is saved separately regardless.
• Background music: If the video has no audio (sound=False in the clip request), user is asked whether to add background music (optional).
• Platform resize: Video is automatically resized for each target platform (letterbox/pillarbox with black padding, no stretching)

Save all final assets to {post_folder}/ -- keyframes in keyframes/, video versions in versions/, platform-resized final videos in final/:

• Video files (.mp4) — post-processed and resized per platform
• Script — timestamped narration/dialogue
• Storyboard — shot-by-shot visual breakdown with keyframe references
• SRT subtitle file (.srt) — for captioned playback

Keyframe and reference inputs — what generate_video.py implements

Read from scripts/generate_video.py. Never describe the video as doing more than this.

Practical consequence: Stage 3's approved last frame is a real model input on the kling rung only. Under --provider auto, a supplied --last-image makes the chain try kling first (without one, auto sends clips of 8 seconds or less to veo whenever Google credentials exist, and veo cannot take an end frame). Passing --provider kling says the same thing explicitly; an explicit --provider veo or higgsfield still wins and leaves the frame unused. Then read video.last_frame_used in the result. true means the end image was sent. false means it was not, and last_frame_note says which rung made the clip: tell the user, put the intended ending into the motion prompt in words, and do not describe the clip as landing on the approved frame. Even when it was sent, the model is guided toward the frame rather than guaranteed to reach it — look at the clip's final seconds before the user approves it.

Output Per Video Post

Video Types

Rules

• Every stage requires explicit user approval before advancing
• --script-only skips Stages 2-4 and generates script + storyboard only
• --thumbnail generates a video thumbnail via compose-creative (independent of the pipeline)
• AI video clips are never auto-saved; user must confirm the final selection
• Thumbnails use the same creative mode system as static images
• All assets save to {post_folder}/ -- keyframes in keyframes/, video versions in versions/, final video in final/

Timeout & Fallback

• AI video generation (Stage 4): 300-second timeout (the video model can take several minutes for high-quality output)
• Keyframe generation (Stages 2-3): 60-second timeout per image
• If video generation fails or times out, deliver script + storyboard + keyframes as fallback