flora-mcp-skills: Skill for Claude Code

.agents/skills/flora-pdp-deck/SKILL.md

flora-pdp-deck is a skill for Claude Code from florafauna-ai/flora-mcp-skills. It costs 147 tokens per session (6,792 once invoked), scanned A, original, MIT.

A FLORA workflow for creating a product-page image set and an annotated PDF from product photographs, with optional model images.

In plain words
What is it for?
Use it to prepare product photos for a shoppable product page, generate context or on-model views, and assemble an A4 sales or review deck.
Why use it?
It helps keep the product's appearance consistent across studio plates, model views, and presentation materials.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: 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-pdp-deck/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-pdp-deck

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/florafauna-ai/flora-mcp-skills/flora-pdp-deck"><img src="https://agentmods.dev/badge/skills/florafauna-ai/flora-mcp-skills/flora-pdp-deck.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 147 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,792 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Anti-Refusal · line 336
    Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.
    Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 $0.00147 $0.06792
Opus 5 $0.00073 $0.03396
Sonnet 5 $0.00029 $0.01358
Haiku 4.5 $0.00015 $0.00679

Measured 12d ago against content hash 83a3508b8208, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

flora-pdp-deck scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

runs API over curl needs the API key. Media urls do not.
.agents/skills/flora-pdp-deck/SKILL.md · 547 lines

How it starts

The opening of the file, as written. The whole thing — 547 lines — stays where its author put it; the contents beside it link to each section on GitHub.

flora-pdp-deck

Self-contained. The deck builder is at the foot of this file; write it out and run it.

What it is

Not an image generator. A consistency engine. The product exists; the job is putting it in front of a camera many times without it drifting between frames.

The product is reference-locked. The world and the pose are generated. A seam moving, a strap ending somewhere new, a colour drifting — that is a fail.

What you can get from what you have

Start here. What the user hands you decides what you can honestly promise, and the limits are not obvious.

one product photo        1 clean plate + N on-model or context frames + a deck
  + a model frame        the same, with a real person holding or wearing it
several real photographs one plate per photograph, plus the above

A single reference cannot be rotated by asking. The SHOT: line changes framing; it does not turn the product. Measured — four plates from one photo, byte-identical prompt block, only the shot line varying:

mean absolute grey difference, 0 = identical
  three-quarter  vs  rear 180 deg      3.21    <- opposite faces requested
  front          vs  three-quarter     6.39
  each plate     vs  the reference     8.06 - 8.74

The plates differed from each other less than each differed from its own source. Four requested angles, four near-duplicates. On an asymmetric product it shows directly: a wax drip specified on one side stayed on that side in the frame asked to show the opposite face.

So from one photo: generate one plate, not four. Then spend the budget on on-model and context frames, where the composition genuinely changes and the model has real work to do. Say this to the user before firing. Four billed duplicates is the expensive way to learn it.

Intake — the image is in the chat, not in FLORA

The user drops a photo into the conversation. It is not in FLORA. Nothing generates until you put it there, and this is the step that stalls a run.

Read the full file on GitHub · 547 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. 12d ago First seen · 547 lines · 147 tokens per session scan A 83a3508b8208

Subscribe to this mod's changes

flora-pdp-deck is a skill published in the GitHub repository florafauna-ai/flora-mcp-skills (8 stars, last pushed today), licensed MIT. It adds 147 tokens to every session and 6,792 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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