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.
npx agentmods add skills/hashgraph-online/awesome-codex-plugins/codex-skin-pack-installernpx skills add hashgraph-online/awesome-codex-plugins --skill codex-skin-pack-installergit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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.
[](https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/codex-skin-pack-installer)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/codex-skin-pack-installer"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/codex-skin-pack-installer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00125 | $0.00893 |
| Opus 5 | $0.00063 | $0.00447 |
| Sonnet 5 | $0.00025 | $0.00179 |
| Haiku 4.5 | $0.00013 | $0.00089 |
Grade A, and why
codex-skin-pack-installer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Skin Pack Installer
Install verified Codex theme and skin packs without publishing private workspace screenshots or editing the signed app bundle.
This is a Skills.sh / npx skills installer for public-safe Codex desktop themes. It is meant for users searching for "Codex theme", "Codex skin", "install Codex theme", or "Codex Dream Skin packs" who want a real downloadable theme pack instead of a private screenshot.
Quick Start
Install this skill:
npx skills add ChannelerH/codex-skin-packs --skill codex-skin-pack-installer --global --agent codex --yes
Use the helper script to download and stage a pack:
python3 "$CODEX_SKILL_DIR/scripts/fetch_skin_pack.py" caishen-readable
The script downloads from the public GitHub release, validates the zip, extracts it to ~/.codexthemes/packs/<slug> by default, and writes a source manifest.
List available packs:
python3 "$CODEX_SKILL_DIR/scripts/fetch_skin_pack.py" --list
Workflow
- Identify the requested pack slug. If the user gives a vague style, list available packs and pick the closest match.
- Run
scripts/fetch_skin_pack.py <slug>unless the user already has a local pack folder. - Inspect the staged folder. It must contain
theme.json,background.png, and preferablyREADME.md. - Apply the staged pack through the user's active Codex theme manager or Codex Dream Skin workflow. Do not modify
app.asar, signed application bundles, private task data, or private screenshots. - Verify the Codex Home, Task, Diff, and Composer states for readability. If a live UI check is not possible, say that clearly and provide the staged path plus manual apply guidance.
- Always finish with the restore path: use the active theme manager's restore command or restore the default Codex appearance from the saved/original theme state.
Pack Slugs
caishen-readable- lower-strain fortune skin and recommended first pack.caishen-lite- soft fortune skin with readable working areas.caishen-max- brighter fortune skin for short immersive sessions.global-founder-bright- bright international growth/workspace skin.export-night- dark export-ops skin.mythic-guardian-noir- dark mythic focus skin.
What ships with it
2 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.
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.
- today First seen · 81 lines · 125 tokens per session scan A 1eaefcaa1c0e
codex-skin-pack-installer is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (924 stars, last pushed today), licensed Apache-2.0. It adds 125 tokens to every session and 893 once invoked, about $0.0006 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 2026-09-05.
Other skills, from other repositories
search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
similar-resources
Given a Japanese NLP GitHub repo or Hugging Face model/dataset (URL / owner/repo / tool name), find repositories or models/datasets that do the same or related processing. Mines the bundled dataset for content-similar items, then expands via web research across both GitHub and Hugging Face, then merges and re-ranks.
sprr
Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".
bprr
Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.
reverse-engineering-android-malware-with-jadx
Reverse engineers malicious Android APK files using JADX decompiler to analyze Java/Kotlin source code, identify malicious functionality including data theft, C2 communication, privilege escalation, and overlay attacks. Examines manifest permissions, receivers, services, and native libraries. Activates for requests…
implementing-code-signing-for-artifacts
This skill covers implementing code signing for build artifacts to ensure integrity and authenticity throughout the software supply chain. It addresses signing binaries, packages, and containers using GPG, Sigstore, and platform-specific signing tools, establishing trust chains, and verifying signatures in deployment…