flora-mcp-skills: Skill for Claude Code

.agents/skills/flora-brand-ad-pipeline/SKILL.md

flora-brand-ad-pipeline is a skill for Claude Code from florafauna-ai/flora-mcp-skills. It costs 149 tokens per session (3,042 once invoked), scanned A, original, MIT.

A four-stage workflow for creating branded product-launch ads, archiving the master in Google Drive, hosting a copy in Supabase, and creating paused Meta Ads creatives for human review.

In plain words
What is it for?
Use it to produce launch ad batches, preserve their source files, create hosted copies, and prepare Meta campaigns that remain paused until someone approves them.
Why use it?
It keeps brand details and progress consistent across generation, storage, hosting, and ad setup, while preventing later stages from running before earlier ones are proven.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument; installed under .agents/ (shared by several agents).

This is florafauna-ai/flora-mcp-skills's own configuration. It tells Claude Code how to work on flora-mcp-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything flora-mcp-skills configures →

Part of the flora-mcp-skills plugin — 15 skills shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to florafauna-ai/flora-mcp-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/florafauna-ai/flora-mcp-skills/main/.agents/skills/flora-brand-ad-pipeline/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/florafauna-ai/flora-mcp-skills

Made for: Claude Code.

Or install flora-mcp-skills, the plugin that ships this one along with the rest of its 15 skills.

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 flora-brand-ad-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-pipeline/github.svg)](https://agentmods.dev/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-pipeline)
Your own site
<a href="https://agentmods.dev/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-pipeline"><img src="https://agentmods.dev/badge/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-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 flora-brand-ad-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-pipeline"><img src="https://agentmods.dev/badge/skills/florafauna-ai/flora-mcp-skills/flora-brand-ad-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 149 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,042 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00149 $0.03042
Opus 5 $0.00075 $0.01521
Sonnet 5 $0.00030 $0.00608
Haiku 4.5 $0.00015 $0.00304

Measured 12d ago against content hash 9552d416b0b4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

flora-brand-ad-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 12d 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.

.agents/skills/flora-brand-ad-pipeline/SKILL.md · 274 lines

How it starts

The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.

flora-brand-ad-pipeline

Attribution. Pass skill: "flora-brand-ad-pipeline" on every FLORA call you make while running this skill — execute included — along with a skill_run_id you invent once when the run starts and reuse for the rest of it. Both are reporting only: they change nothing about the call or its result.

What it is

Not a creative assistant. A conveyor. A product line goes in one end; paused ads, an archived master and a hosted CDN copy come out the other, with one record tying every ad back to the generation that made it.

FLORA is one stage of four. Most of what makes this reliable is not the generation — it is refusing to advance a stage that has not been proven, and keeping enough state on disk that a re-run repairs the pipeline instead of duplicating it.

The law

The brand is an input, not an instruction.

Fixed colours, a price that must always be visible, product reference shots: these decay the moment they are carried as prose an agent retypes each run. Agents paraphrase. A paraphrased brand drifts, and it drifts silently across every item in a batch — nobody sees it until a human opens the ads.

So the brand never lives in this file, and never lives in a prompt you compose:

  • The treatment lives in a saved FLORA technique. A technique's steps, prompts and model choices are fixed by its author, so it gives the same treatment every time and the agent cannot rewrite the middle of it. Whatever can move out of prose and into a technique, move.
  • The product lives in a reference image. Reference-locked, never re-described.
  • The values live in brand.json. Colours, price format, placement sizes, product reference ids. See reference/brand.md. Read it; do not inline it.
  • The price is composited, not generated. No image model renders a price string reliably, and "price always visible" is a compliance requirement, not a style note. Overlay it deterministically and the question becomes a boolean.

Read the full file on GitHub · 274 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 274 lines · 149 tokens per session scan A 9552d416b0b4

Subscribe to this mod's changes

flora-brand-ad-pipeline is a skill published in the GitHub repository florafauna-ai/flora-mcp-skills (8 stars, last pushed today), licensed MIT. It adds 149 tokens to every session and 3,042 once invoked, about $0.0007 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 2026-08-31.

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