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lifestyle-ad

lifestyle-ad

github.com/postplusaiMarketing & growth27500 installsUpdated 1d ago
Repository

About lifestyle-ad

lifestyle-ad is a skill for developing lifestyle ad concepts and shot scripts for creative and production planning. It creates a Camera Grammar Plan and shot table, then hands the approved script to an appropriate production workflow.

Key features

  1. 01Ground concepts in product context
  2. 02Create a Camera Grammar Plan
  3. 03Write a shot-by-shot script
  4. 04Include a user approval checkpoint
  5. 05Hand approved work to production

Use cases

  1. 01Turn product facts into lifestyle ad concepts
  2. 02Plan shots for an advertising production
  3. 03Continue to image or video production after script approval

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/postplusai/postplus-skills --skill lifestyle-ad

After installing, type/lifestyle-adin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
camera-grammar.md
shot-script-rubric.md
workflow-handoff.md

Details

From the project README

Lifestyle Ad

Purpose

Create state-led lifestyle ad concepts and shot scripts. The product should feel like part of a person's taste, rhythm, and composure, not a feature demo.

Use this skill to turn product facts, brand docs, reference ads, or rough feature ideas into:

  1. A Camera Grammar Plan.
  2. A shot-by-shot script.
  3. A user approval checkpoint.
  4. Direct handoff to the right production skill after approval.

Workflow

1. Ground The Brief

Read the smallest useful source context first:

  • brand, product, claim-boundary, persona, script, or reference files supplied by the user
  • prior ad-analysis files or benchmark notes when explicitly relevant
  • product reference, creator reference, audio reference, duration, model, or resolution preferences if provided

Lock these before writing:

  • product capability
  • desired visible user state
  • audience
  • proof available
  • claim boundaries
  • visual world
  • output format and duration target when supplied
2. Design The Camera Grammar

Read references/camera-grammar.md.

Produce a Camera Grammar Plan with these fields:

  • status_to_make_visible
  • body_product_relationship
  • dominant_framing
  • motion_ratio
  • pressure_carrier
  • product_gesture
  • proof_style
  • sound_world
  • text_restraint
  • final_identity_line

Do not force a fixed shot order, scene type, phrase, product category, or ending formula. Choose grammar that fits the current brand and product.

3. Write The Shot Script

Read references/shot-script-rubric.md.

Return a shot table with exactly these columns:

time | visual | framing/composition | action | sound | subtitle/text | purpose

Keep each row concrete enough for filming or video-generation prompting. Use restrained text and make the product action socially natural.

After the shot script, ask the user whether this script direction is OK.

4. On Approval, Handoff Directly

If the user approves the script, read references/workflow-handoff.md and immediately hand off to the right production runner.

Use $video-batch-runner by default: it turns the approved shot script into hosted video renders. This is the standard path when the user simply says to continue after approving the script.

Use $image-batch-runner first when the approved script needs still assets before video: persona images, product lifestyle stills, first-frame candidates, scene images, or light consistency edits. Those stills then feed the video renders.

Pass the approved shot script, Camera Grammar Plan, brand constraints, product facts, claim boundaries, and any provided references as locked creative context. Do not output a separate production brief and do not ask a second "generate?" confirmation.

Let the downstream production runner handle missing product, creator, audio, model, resolution, route validation, and asset validation.

Quality Bar

  • Start from human state and tension, not from a product announcement.
  • Let the viewer infer capability from composure, behavior, and light proof.
  • Use specific environment pressure instead of broad pain-point copy.
  • Make product gestures ordinary: touch, adjust, lift, place, glance, close, carry.
  • Treat UI, results, labels, and text as proof glimpses, not tutorials.
  • Prefer identity-style endings over hard CTAs unless the user asks for direct response.

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