ai-image-realism

ai-image-realism is a skill for Claude Code from sickn33/agentic-awesome-skills. It costs 30 tokens per session (3,781 once invoked), scanned A, original, MIT.

A tool for making existing AI-generated portraits, product pictures, and marketing images look more natural. It sends the work to the paid Beatra hosted service.

In plain words
What is it for?
Use it to improve AI images for advertising, products, portraits, and other paid hosted work.
Why use it?
It addresses common visual problems such as plastic-looking skin, malformed hands and faces, repeated textures, and uneven lighting.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument; mentions Claude Code; mentions Codex.

Part of the agentic-awesome-skills plugin — 256 skills shipped together

Good fit Use it to improve AI images for advertising, products, portraits, and other paid hosted work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sickn33/agentic-awesome-skills/ai-image-realism
About the project

AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.

sickn33/agentic-awesome-skills · 48,337 stars · on GitHub · aaskills.tech

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 sickn33/agentic-awesome-skills --skill ai-image-realism
Clone the repo
git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills

Made for: Claude Code.

Or install agentic-awesome-skills, the plugin that ships this one along with the rest of its 256 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 ai-image-realism

README.md
[![agentmods](https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/ai-image-realism/github.svg)](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/ai-image-realism)
Your own site
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/ai-image-realism"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/ai-image-realism/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 ai-image-realism

Your own site · 80×15
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/ai-image-realism"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/ai-image-realism.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,781 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 $0.00030 $0.03781
Opus 5.5 $0.00012 $0.01512
Sonnet 5.5 $0.00006 $0.00756
Haiku 4.5 $0.00003 $0.00378

Measured yesterday against content hash 46f5e265a9f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-image-realism 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 yesterday.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/agentic-awesome-skills-claude/skills/ai-image-realism/SKILL.md · 287 lines

How it starts

The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Image Realism Skill

Overview

Make existing AI portraits, product images, and marketing visuals look more natural by fixing plastic skin, malformed hands and faces, repeated textures, and inconsistent lighting, from inside Claude Code, Codex, or OpenClaw. The work is produced on the hosted, paid Beatra service (mcp.beatra.ai).

This catalog entry is a reviewed pointer, not the executable package. It contains no client code and performs no Beatra operation by itself. The package it points to bundles three standard-library Python scripts that make network calls and store a credential. It has no self-updater: it never downloads code and never changes its own files. Read Install and Security & Safety Notes before activating it.

Pinned identity Value
Package ai-image-realism 0.3.6
Source commit beatra-ai/ai-image-realism-skill@0b29222 (full SHA 0b29222a61c52917887efa40d39e100683b03625)
Package tree d7b1f2866555aae60d53de35293437b2ecbdb6d6 (Git tree ID of skills/ai-image-realism at that commit)
License MIT No Attribution (MIT-0)

The pinned tree holds regular files only (no symlinks, no executable bits, no binaries). Confirm that with the inspect commands below.

When to Use This Skill

  • Use when the user explicitly wants an existing image retouched on Beatra and accepts that it is paid.
  • Use when the host agent can view the source image and the user has agreed to send it to a third party.
  • Do not use for local-only image editing or when no paid render was approved.

Install (pinned, verified, approved twice)

Step 1: Fetch the pinned tree into a review directory

Explain that this fetches an external package from github.com, then ask for approval. Only after approval:

set -e
umask 077
review_dir="$(mktemp -d)"
cd "$review_dir" || exit 1
git clone --quiet --filter=blob:none --no-checkout https://github.com/beatra-ai/ai-image-realism-skill.git src
git -C src checkout --quiet 0b29222a61c52917887efa40d39e100683b03625 -- skills/ai-image-realism
test "$(git -C src rev-parse '0b29222a61c52917887efa40d39e100683b03625:skills/ai-image-realism')" = 'd7b1f2866555aae60d53de35293437b2ecbdb6d6' && echo TREE-OK

Read the full file on GitHub · 287 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. yesterday First seen · 287 lines · 30 tokens per session scan A 46f5e265a9f3

Subscribe to this mod's changes

ai-image-realism is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,337 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 3,781 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-22.