Paw Cra Design Batch

Batch Design Production

Overview

Batch visual production for campaigns — transforms a content calendar or campaign brief into a complete set of platform-ready visual assets. This workflow handles multi-asset production runs: parsing the brief, building a production queue, generating each asset with brand validation, and delivering an organized bundle with a machine-readable manifest.

Args: Accepts --headless / -H for full autonomous batch production without interaction.

Output: Organized campaign asset bundle folder + batch-manifest.json listing every produced asset with specs.

On Activation

Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml (root level and cra section). Resolve and apply throughout the session (defaults in parens):

• {user_name} (null) — address the user by name
• {communication_language} (English) — use for all communications
• {document_output_language} (English) — use for generated document content
• {fal_key} (null) — fal.ai API key for image generation
• {output_directory} (.pawbytes/creative-suites) — base output path

Load shared agency memory from {project-root}/.pawbytes/creative-suites/index.md. Load active brand guidelines from .pawbytes/creative-suites/brands/{active-brand}/guidelines.md.

Knowledge Base: Check {project-root}/.pawbytes/creative-suites/knowledge/index.md for previously researched platform specs and design guides.

Tool Verification:

• fal_key availability (required — no batch production without it)
• ffmpeg availability (optional — needed only for animated carousels)
• Puppeteer/Playwright availability (optional — for template rendering)

If --headless or -H is passed, execute the full pipeline without interaction. Load ./references/autonomous-batch.md for headless execution protocol.

Otherwise, confirm the brief/calendar with the user before beginning production.

---

Pipeline

The batch production pipeline runs in sequential phases. Each phase completes fully before the next begins. In headless mode, all phases execute without pauses. In interactive mode, a review gate after generation allows the user to approve, revise, or reject before final bundling.

Step 1 — Brief Intake

Load ./references/brief-intake.md

Parse the incoming content calendar or campaign brief. Extract:

• Total number of assets required
• Per-asset specs: platform, format, dimensions, content/copy, visual direction
• Brand reference (which brand guidelines to load)
• Campaign name and any naming conventions
• Priority or ordering preferences

If the input is a content calendar, each row becomes an asset in the production queue. If the input is a campaign brief with deliverable descriptions, decompose it into individual asset specs.

Output: Structured asset list ready for queue building.

Step 2 — Brand & Campaign Context Load

Load brand guidelines for the specified brand. Load any existing campaign assets from .pawbytes/creative-suites/brands/{brand}/campaigns/{campaign}/assets/ to understand what already exists and maintain visual consistency.

If the campaign has approved copy/scripts in .pawbytes/creative-suites/brands/{brand}/campaigns/{campaign}/scripts/, load those for use in asset generation.

Output: Brand context and existing campaign context loaded into working memory.

Step 3 — Production Queue Build

Load ./references/queue-builder.md

Build an ordered production queue from the parsed asset list. Group assets by platform and format to enable efficient batch generation (same-platform assets can share style seeds and templates).

For each queue item, resolve:

• Platform specifications (dimensions, safe zones, format)
• Template selection (if using code-based templates)
• AI generation parameters (model, style, seed strategy)
• Text overlay requirements
• Export format and naming convention

Apply sequential naming: {campaign}_{platform}_{type}_{NNN}.{ext} (e.g., summer-sale_instagram_post_001.png).

Output: Ordered production queue with fully resolved specs per asset.

Step 4 — Batch Generation Loop

Load ./references/batch-generation.md

For each asset in the production queue:

1. Load platform specs — Confirm dimensions, safe zones, format requirements
2. Generate AI imagery — Use fal.ai with the resolved prompt and parameters. Use the Designer's AI model selection guide for model choice. Download all generated images to local paths.
3. Apply template/text overlay — If the asset uses a code-based template, render the HTML/CSS overlay with the generated background. If pure AI generation, apply any text overlays via image editing.
4. Brand validate — Check output against brand guidelines: correct colors, typography, logo placement, visual style consistency. Flag any deviations.
5. Export with sequential naming — Save to the campaign asset folder with the naming convention from Step 3.

Track progress: log each completed asset to a running tally. If an asset fails generation, log the failure with reason and continue to the next asset — do not halt the entire batch.

Output: Generated assets in the campaign folder + per-asset generation log.