Compose Creative

---
name: compose-creative
description: "Core creative engine — turns a calendar post into finished images or video using 4 modes (anchor-compose, enhance-extend, style-referenced, pure-creative) with brand assets, AI generation, and human approval before credits are spent. Triggers on \"/compose-creative\", \"generate the creative\", \"make the image for P07\", \"produce this post\", \"create the visual\", \"compose this\", or any time a calendar post needs its creative produced. Overlay text follows the pairing rule — it never echoes the caption."
argument-hint: "[--post <id>] [--all] [--variant b]"
effort: max
user-invocable: true
---

# /socialforge:compose-creative — Creative Production Engine

The core production skill. Takes asset matching results and produces visual and video assets for each post according to its assigned creative mode, using a staged human-in-the-loop approval flow.

## 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.

## The 4 Creative Modes

### MODE 1: ANCHOR_COMPOSE
Brand asset is the untouchable center. AI generates scene around it.
1. Remove background from brand asset (rembg)
2. Generate surrounding scene via AI using brand style references
3. Composite asset onto generated scene (Pillow)
4. Add shadow/reflection for natural placement
5. Add text overlay + logo
6. Resize per platform

### MODE 2: ENHANCE_EXTEND
Brand asset is the foundation. AI modifies periphery only.
1. Feed real image to AI edit endpoint
2. AI extends/enhances while preserving core subject
3. Verify core subject preservation
4. Add overlay + resize

### MODE 3: STYLE_REFERENCED
No brand asset composited. Style reference photos guide AI generation.
1. Load 2-8 brand style reference images
2. Construct 5-layer prompt (brand identity, post context, creative direction, image rules, technical)
3. Feed references + prompt to AI generation
4. Quality review — does output match brand DNA?
5. Add overlay + resize

### MODE 4: PURE_CREATIVE
Full AI generation with only text prompt + brand colors/mood.
1. Construct prompt from brief + brand-config visual style
2. Generate (text-only, no reference images)
3. Quality review
4. Add overlay + resize

## Reference images and keyframes — what the scripts actually do

Read from `scripts/generate_image.py`, `scripts/edit_image.py` and `scripts/generate_video.py`. This skill promises only what those scripts implement.

| Input | How to pass it | What is true today |
|---|---|---|
| Style references for a new image (STYLE_REFERENCED) | `generate_image.py --references <path> [<path> ...]` — the first 14 are read | Sent to the **primary** image provider only. The fallback providers receive the prompt and aspect ratio, **not** the references: when the result carries `fallback_from` and references were supplied, it also carries `references_used: 0`, `references_dropped: <n>` and a `references_note` — the image is **not** style-referenced. Tell the user, and fix the primary provider's credentials rather than accepting a reference-less image as a style-referenced one. |
| References alongside an image being edited (ENHANCE_EXTEND) | `edit_image.py --image <src> --instruction "..." --references <path> ...` — first 14 | Supported. There is no fallback chain for edits. (`generate_image.py --edit` takes no references.) |
| First frame for video | `generate_video.py --image <path>` | Supported by every video provider in the chain; one of them requires it. See `/socialforge:generate-video`. |
| Last frame for video | `generate_video.py --last-image <path>` (with `--generate-video`) | Sent to the `kling` rung as the clip's end image; no other rung takes one. The result's `video.last_frame_used` says whether it was sent — `false` (with a `last_frame_note`) means the clip was not steered to the approved last frame. See `/socialforge:generate-video`. |
| Reference images for video | none | **Not wired** through `generate_video.py` — no flag exists. See `/socialforge:generate-video`. |

Two caveats from the code: file type is set from the extension (`.jpg`/`.jpeg` as JPEG, everything else as PNG), so pass JPEG or PNG and convert WebP first; and `references_used` is the number of files actually read and sent, not the number of paths passed. When it is lower than what you passed, the result says why: `references_missing` lists the paths that do not exist (they are not sent, and there is no error), `references_over_limit` counts the paths past the 14-file limit, and `references_dropped` plus `references_note` mean a fallback provider made the image. Read those fields before treating an image as style-referenced.

## Prerequisites

- `asset-matches.json` must exist (generated by `/socialforge:match-assets` -> match_assets.py)
- `calendar-data.json` must exist (generated by `/socialforge:parse-calendar`)
- `brand-config.json` must exist for active brand
- `cost-log.json` initialized (via status_manager.py --action init-month)
- Valid credentials for the image provider (Vertex AI, alias `latest-image-balanced-google`) and the video provider (WaveSpeed, alias `latest-video-wavespeed`) via credential_manager.py. Which model each alias resolves to today: `python scripts/generate_video.py --list-models`.

If any prerequisite is missing: "Run `/socialforge:match-assets` first — creative production needs asset matching results."

## Process (For Each IMAGE Post) — 4-Stage Approval Flow

### Stage 1: Creative Direction (No API Call)
Present 2-3 creative direction options to the user. Each option includes:
- A description of the visual concept
- Mood, color palette, and composition approach
- How the brand asset will be used (per the assigned creative mode)
- Rough reference to style/tone
- **Overlay text, written against the pairing rule**: the overlay and the
  caption do different jobs and never echo each other. The overlay stops the
  scroll — a promise, a number, a tension in a few words. The caption (written
  later by adapt-copy) pays it off with context and the CTA. If the proposed
  overlay reads like the caption's first line, it is the wrong overlay — the
  quality reviewer flags this pairing as a Copy Quality failure downstream, so
  catch it here before credits are spent.

No image generation happens here. The user picks a direction before any credits are spent.

### Stage 2: Confirm Details
Once the user selects a direction, confirm the specifics before generating:
- Final prompt details and any refinements the user wants
- Aspect ratio and platform targets
- Text overlay copy and placement preferences
- Any special instructions (e.g., "warmer tones", "more negative space")

User explicitly approves to proceed to generation.

### Stage 3: Generate and Select (image provider, Vertex AI)
- Generate 2-3 image versions based on the confirmed direction
- Show all versions inline via the Read tool so the user can compare
- User picks their preferred version (or requests another round with adjustments)
- Max 3 generation rounds per post before escalating

### Stage 4: Post-Process and Save
After the user selects their preferred image:
1. Apply text overlay via compose_text_overlay.py
2. Apply logo per brand-config.json (position, opacity, size, platform exclusions)
3. Resize per platform via resize_image.py
4. Save final assets to the post-specific folder: `{post_folder}/final/`
5. Update status-tracker.json
6. Log prompt to `shared/prompt-logs/`
7. Track API cost in cost-log.json

## Process (For Each VIDEO Post) — 5-Stage Approval Flow

### Stage 1: Video Concept (No API Call)
Present 2-3 video concept ideas to the user. Each option includes:
- A narrative arc or visual concept for the short-form video
- Description of the opening frame, motion/transition, and closing frame
- Mood, pacing, and style notes
- How brand assets or style references will be incorporated

User picks a concept before any generation begins.

### Stage 2: First Frame Generation (image provider, Vertex AI)
- Generate 2 first-frame options based on the selected concept
- Show both inline via the Read tool
- User picks their preferred first frame (or requests adjustments)

### Stage 3: Last Frame Generation (image provider, Vertex AI)
- Generate 2 last-frame options that complement the approved first frame
- Show both inline via the Read tool
- User picks their preferred last frame (or requests adjustments)

### Stage 4: Video Generation (WaveSpeed, `latest-video-wavespeed`)
- Generate 2 video versions from the approved frames (`generate_video.py --generate-video --image <first-frame> --last-image <last-frame>`). The last frame reaches the video model only on the `kling` rung — pass `--provider kling` when the clip must end on it, and read `video.last_frame_used` in the result before presenting a clip as landing on it (see "Reference images and keyframes" above).
- Use the video provider chain via generate_video.py
- Show both versions for user review
- User picks their preferred video (or requests another round)
- Max 3 generation rounds before escalating

### Stage 5: Post-Process + Save
After the user picks the final video, post-processing runs before saving:
1. **Watermark:** Logo overlay is automatically added to the video via video_postprocess.py
2. **Subtitles:** User is asked whether to burn subtitles into the video (optional). SRT was already generated from the script and is saved separately regardless.
3. **Background music:** If the video has no audio (sound=False in the clip request), user is asked whether to add background music (optional).
4. **Platform resize:** Video is automatically resized for each target platform (letterbox/pillarbox with black padding, no stretching)
5. Save all platform versions to `{post_folder}/final/`
6. Save alternatives to `{post_folder}/versions/`
7. Update status-tracker.json
8. Log prompt and generation parameters to `shared/prompt-logs/`
9. Track API cost in cost-log.json

## Batch Mode (/socialforge:generate-all)

When processing all posts via `/socialforge:generate-all`, the staged approval flow uses **group-based approval** to avoid per-post bottlenecks:

1. **Group posts by creative mode** — all ANCHOR_COMPOSE posts together, all PURE_CREATIVE together, etc.
2. **Stage 1 in bulk** — present creative direction options for each post in the group at once. User reviews and selects directions for the entire group before generation begins.
3. **Stage 2 confirmation** — confirm details for the group. User can adjust individual posts or approve the batch.
4. **Stage 3 generation** — generate images/videos for the group sequentially. After each post's variants are generated, show them inline. User can approve, request regeneration, or skip.
5. **Stage 4/5 post-processing** — all approved posts are post-processed together (logo, resize, save).

Progress indicator during batch:
```
[GROUP 1: ANCHOR_COMPOSE — 8 posts]
  Presenting directions... awaiting approval

[GROUP 2: STYLE_REFERENCED — 12 posts]
  Queued — waiting for Group 1

[GROUP 3: VIDEO — 4 posts]
  Queued — waiting for Group 2
```

Posts that are skipped or fail after 3 rounds are collected into a "needs attention" list presented at the end of the batch.

## Rules
- **Brand assets are SACRED** — never modify the core subject in ANCHOR_COMPOSE
- **No text in AI-generated images** — text is always added via compose_text_overlay.py
- **Logo overlay** per brand-config.json (position, opacity, size, platform exclusions)
- **Every generated image/video requires user approval** at each stage before proceeding
- **No API calls before Stage 1 approval** — creative direction is confirmed before spending credits
- **Max 3 generation rounds** per post before escalating to user
- **Show all variants inline** via the Read tool so the user can visually compare

## Progress Indicators

```
[3/28] Post P03 — IMAGE — ANCHOR_COMPOSE
  Stage 1: Presenting 3 creative directions...
  [User selects Direction B]
  Stage 2: Confirming details...
  [User approves]
  Stage 3: Generating 3 variants (image provider, Vertex AI)...
    Variant A... done
    Variant B... done
    Variant C... done
  [Images shown inline — user selects Variant B]
  Stage 4: Post-processing...
    Text overlay... done
    Logo... done
    Resize (IG, FB, LinkedIn)... done
    Saved. done

[4/28] Post P04 — VIDEO — STYLE_REFERENCED
  Stage 1: Presenting 2 video concepts...
  [User selects Concept A]
  Stage 2: Generating 2 first frames (image provider, Vertex AI)...
  [User selects Frame 1]
  Stage 3: Generating 2 last frames (image provider, Vertex AI)...
  [User selects Frame 2]
  Stage 4: Generating 2 video versions (WaveSpeed)...
  [User selects Video A]
  Stage 5: Saving final...
    Saved. done
```

## Scripts Used
- generate_image.py | compose_image.py | edit_image.py
- generate_video.py | credential_manager.py
- resize_image.py | compose_text_overlay.py | verify_brand_colors.py

## Timeout & Fallback
- Image generation (image provider, Vertex AI): 60-second timeout per image. Retry once with simplified prompt.
- Video generation (WaveSpeed): 300-second timeout per video, matching `generate_video.py`. Retry once with reduced parameters.
- Background removal: 30-second timeout. If fails, flag for manual masking.
- Compositing: 15-second timeout. If Pillow fails, save components for manual assembly.
- Total per image post: 5-minute cap. If exceeded, mark as `production_timeout` and move to next.
- Total per video post: 8-minute cap. If exceeded, mark as `production_timeout` and move to next.
- **Staged approval pauses do not count against timeout** — the clock runs only during active generation and processing.