branded-reel-pipeline

branded-reel-pipeline is a skill for Claude Code from S3YED/appie-kit. It costs 183 tokens per session (2,976 once invoked), scanned A, original, MIT.

A workflow for producing branded short-form videos from a script, visual assets, music, voiceover, and real dashboard data. It assembles these parts into a finished reel with consistent brand styling.

In plain words
What is it for?
Use it to make branded reels, analytics videos, dashboard-based videos, and other short social clips with captions, narration, visuals, and live data.
Why use it?
It combines creative production with live business information, so the video can show real screens and numbers instead of invented examples.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 reference/run-pipeline.py --brief templates/brief.example.json.

Good fit Use it to make branded reels, analytics videos, dashboard-based videos, and other short social clips with captions, narration, visuals, and live data.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/S3YED/appie-kit
agentmods
npx agentmods add skills/s3yed/appie-kit/branded-reel-pipeline

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for branded-reel-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/s3yed/appie-kit/branded-reel-pipeline/github.svg)](https://agentmods.dev/skills/s3yed/appie-kit/branded-reel-pipeline)
Your own site
<a href="https://agentmods.dev/skills/s3yed/appie-kit/branded-reel-pipeline"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/branded-reel-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for branded-reel-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/s3yed/appie-kit/branded-reel-pipeline"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/branded-reel-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 183 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,976 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00183 $0.02976
Opus 5 $0.00092 $0.01488
Sonnet 5 $0.00037 $0.00595
Haiku 4.5 $0.00018 $0.00298

Measured 8d ago against content hash e11222a405d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

branded-reel-pipeline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/content/branded-reel-pipeline/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Branded Reel Pipeline

Reusable framework that produces a premium short-form brand reel end to end. It is the premium layer on top of media/short-form-video-production (ideation, hook, retention, captions craft). Use those for the creative craft; use this for the premium branded assembly with real on-brand visuals and live data.

The proven stack (do not deviate without reason)

  1. Script — hook-first, retention-structured. Borrow craft from content-creation (Hook→Tension→Payload→CTA) and short-form-video-production. Beat table: t | OST | VO.
  2. Visuals + musichiggsfield-generate skill. GPT Image 2 for hero frames (9:16, 2k, brand palette), sonilo_music for the bespoke bed. Frames are premium connective tissue; live screens carry conversion.
  3. Voiceover — ElevenLabs eleven_v3, stability 0.30, default voice id cjVigY5qzO86Huf0OWal ("Eric"). Key from environment. Calm-operator delivery.
  4. Live-data capturereference/live-data-capture.py (Playwright). Parameterized: URL + auth method + selector / API path. The differentiator: real dashboards, real numbers count up on screen.
  5. Assembly — Remotion with brand-preset tokens (templates/remotion-template/). Parameterized by aspect ratio. Count-ups, curve-draws, glass device frames, the audio-reactive orb. 1080x1920 @ 30fps for 9:16.
  6. Render + verifyremotion renderffprobe confirms duration/resolution/codec.

Input: the brief

A reel is driven by a brief object:

{
  "subject": "Our AI agent that posts daily and tracks every number",
  "brand_preset": "my-brand",
  "format": "9:16",
  "mode": "gated",
  "live_data_source": {
    "url": "https://your-dashboard.example.com/api/analytics?days=30",
    "auth": { "method": "session_token", "mint": "node scripts/mint-session-token.js" },
    "capture": "json",
    "selector": null
  },
  "script": null
}
  • subject (required): what the reel is about.
  • brand_preset (required): a dir under presets/ matching your brand.
  • format: 9:16 (default) | 1:1 | 16:9.
  • mode: gated (default) | auto.
  • live_data_source (optional): { url, auth, capture: json|screenshot, selector }.
  • script (optional): pre-written beat table; if null the pipeline writes one in Stage 1.

Read the full file on GitHub · 202 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 202 lines · 183 tokens per session scan A e11222a405d8

Subscribe to this mod's changes

branded-reel-pipeline is a skill published in the GitHub repository S3YED/appie-kit (9 stars, last pushed 16d ago), licensed MIT. It adds 183 tokens to every session and 2,976 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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