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Avenox Thumbnail

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avenoxai
avenox-thumbnail

Generate high-CTR YouTube thumbnails for a mascot-driven channel using parallel gpt-image-2 jobs via the Codex CLI. Use whenever the user asks for a thumbnail, cover, or thumbnail alternatives for a video, wants their mascot on a cover, or asks to retrofit new thumbnails onto old videos. Produces on-model mascot + a big 2-4 word hook + tool logos + high-contrast covers, saved 1280x720 ready for YouTube A/B testing.

Overview

Publisheravenoxai
Repositoryavenoxskills
Skill nameavenox-thumbnail
Stars
105
Forks
6
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by avenoxai on GitHub. Read the source before you install it.

Installation

Install the Avenox Thumbnail AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/avenoxai/avenoxskills/tree/main/skills/avenox-thumbnail
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/avenoxai/avenoxskills.git /tmp/avenoxskills
mkdir -p .claude/skills
cp -r /tmp/avenoxskills/skills/avenox-thumbnail .claude/skills/avenox-thumbnail
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Avenox Thumbnail in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Avenox Thumbnail on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Avenox Thumbnail is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Thumbnail Factory

A systematic pipeline for producing scroll-stopping YouTube thumbnails for a mascot-driven channel. It encodes the formula, the working prompt recipe, the hook-pattern playbook, and the hard safety rules learned in production.

Built for anonymous / faceless channels: the mascot is the face, so the covers stay consistent without ever putting a person on screen.

Anonymity rule: never put the creator's real name, personal handle, or likeness on a thumbnail. If the channel is anonymous, the mascot is the identity — breaking that once is not reversible.

Configure before first use

SettingWhereExample
Mascot reference imageassets/mascot-ref.pngsee assets/README.md
Mascot on-model contractreferences/character-and-safety.mdfill in the contract block
Hook languageprompt (HOOK_LANG)Turkish, English, …
Output dir$THUMB_OUT~/Desktop/thumbnails

The formula

Every thumbnail = 4 ingredients, nothing more (3-element rule; blink-test first — if it doesn't read in a quarter second at sidebar size, it failed):

  1. The mascot — on-model, expressive pose that fits the video's emotion.
  2. One 2-4 word hook — MASSIVE bold sans-serif caps, white + ONE accent word, thick black outline. Never duplicate the video title; open a curiosity gap that the title and video close.
  3. Relevant tool logo(s) — so the topic is legible in one glance.
  4. High-contrast modern background — dark + one strong accent color (red = urgency, green = success, blue = tech, purple = automation, gold = money). Bright, saturated, clean.

Design levers (apply, don't just decorate): curiosity gap • negativity/risk • contrast (before/after, ✓/✗) • tangible number or timeframe • authority • one clear focal point • lower-right corner kept clear (YouTube stamps the duration there) • text left / mascot right reads best.

Full hook playbook → references/hook-patterns.md.

Standard workflow

  1. Read the video — title + description/topic. Identify the single most clickable angle.
  2. Propose hooks (unless told "just fire") — 2-3 distinct concept directions: hook words + composition + which logo + which pattern. Let the user pick, or fire all as alternatives.
  3. Fire in PARALLEL — one codex exec gpt-image-2 job per concept, all run_in_background: true in a single message. The user wants alternatives; compute isn't the constraint. Recipe → references/prompt-template.md.
  4. Save all outputs to $THUMB_OUT with descriptive names (<video>-<letter>-<hook>.png).
  5. md5-dedupe after the batch — parallel gpt-image-2 jobs can occasionally return duplicate images. Re-fire any duplicate solo.
  6. Show + recommend — look at each PNG, give an honest verdict, say which title it pairs with, and make an A/B recommendation.
  7. Deliver finals — sips -z 720 1280 <file> (exact YouTube 1280×720, under 2MB) and copy out with a clear name.

Mascot contract

The mascot must stay on-model every time — same colors, same outline weight, same face. That consistency is the brand recognition; a mascot that drifts is worth less than no mascot.

Costumes and props are fine (hat, vest, holding an object) as long as the body and face still read as the same character.

HARD SAFETY RULE — never violate: do NOT pose the mascot with a straight raised outstretched arm / open palm. With a crowd or army behind it, that reads as a fascist salute and will get the thumbnail flagged. Commander/hero poses must keep both arms bent and occupied (holding a banner or sword, hand on hip, fist raised, presenting to the side). Vary poses across a batch — don't reuse an identical stance.

Full contract, expression menu, and safe-pose list → references/character-and-safety.md.

Series rule

For a numbered series, never bake the episode number into the thumbnail — it makes viewers watch only Part 1. Give each episode a distinct, standalone hook that fits that episode, and vary the accent color and pose so the covers don't look like copies of each other. Copy-paste covers read as "already watched".

References

FileRead for
references/prompt-template.mdthe exact working codex exec gpt-image-2 command + prompt skeleton, non-Latin text handling, sizes, output handling
references/hook-patterns.mdthe hook/title pattern library and how to map a video to hooks
references/character-and-safety.mdmascot on-model contract, expressions, poses, safety rules
references/logo-library.mdhow to fetch and rasterize brand logos

Requires the codex-fleet skill for the underlying Codex CLI image runner.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Avenox Thumbnail AI skill do?

Generate high-CTR YouTube thumbnails for a mascot-driven channel using parallel gpt-image-2 jobs via the Codex CLI. Use whenever the user asks for a thumbnail, cover, or thumbnail alternatives for a video, wants their mascot on a cover, or asks to retrofit new thumbnails onto old videos. Produces on-model mascot + a big 2-4 word hook + tool logos + high-contrast covers, saved 1280x720 ready for YouTube A/B testing.

Why use Avenox Thumbnail on TypingMind?

Because you install it once and use it with any model. Avenox Thumbnail is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Avenox Thumbnail in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/avenoxai/avenoxskills/tree/main/skills/avenox-thumbnail. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Avenox Thumbnail?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Avenox Thumbnail?

As many as you like. As long as a model supports skills, you can use Avenox Thumbnail with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Avenox Thumbnail AI skill free?

Yes. It is published on GitHub by avenoxai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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