retocar

retocar is a skill for Claude Code from Livus-AI/Skills-MCP. It costs 26 tokens per session (259 once invoked), scanned A, original, MIT.

A product-image retouching skill for removing wrinkles, improving lighting, cleaning up backgrounds, correcting shadows, and enhancing product photos.

In plain words
What is it for?
Use it to retouch clothing and other product photos, improve colour and lighting, remove distractions, or make an image look more polished.
Why use it?
It helps fix common presentation problems in product images before they are used in shops, catalogues, or marketing.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Good fit Use it to retouch clothing and other product photos, improve colour and lighting, remove distractions, or make an image look more polished.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/livus-ai/skills-mcp/retocar
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Livus-AI/Skills-MCP --skill retocar
Clone the repo
git clone --depth 1 https://github.com/Livus-AI/Skills-MCP

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 retocar

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/livus-ai/skills-mcp/retocar"><img src="https://agentmods.dev/badge/skills/livus-ai/skills-mcp/retocar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 259 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.
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 $0.00026 $0.00259
Opus 5 $0.00013 $0.00130
Sonnet 5 $0.00005 $0.00052
Haiku 4.5 $0.00003 $0.00026

Measured 12d ago against content hash 8c31b1ea47e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

retocar 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.

curl -X POST ${VISUALS_API_URL:-https://visuals-ai.vercel.app}/api/workflow/execute \
skills/visuals/retocar/SKILL.md · 39 lines

What it actually says

Retocar (Retouch) Workflow

Enhance and retouch product images to improve quality, remove wrinkles, fix lighting, or make other improvements.

Input handling

Follow the input handling pattern from change-color skill.

Execute workflow

curl -X POST ${VISUALS_API_URL:-https://visuals-ai.vercel.app}/api/workflow/execute \
  -H "Authorization: Bearer ${VISUALS_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "workflowId": "retocar",
    "inputs": {
      "prompt": "<retouching_instructions>"
    },
    "images": {
      "productImage": "<image_url_or_data_url>"
    }
  }'

Example prompts:

  • "Remove wrinkles from the clothing"
  • "Improve lighting and make colors more vibrant"
  • "Clean up the background and enhance the product"
  • "Fix shadows and make the image more professional"

Poll for completion as described in change-color skill.

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 · 39 lines · 26 tokens per session scan A 8c31b1ea47e8

Subscribe to this mod's changes

retocar is a skill published in the GitHub repository Livus-AI/Skills-MCP (2 stars, last pushed 3mo ago), licensed MIT. It adds 26 tokens to every session and 259 once invoked, about $0.0001 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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