github

github is a skill for Claude Code, Codex from aetox-skills/Aetox-Agents-Team. It costs 43 tokens per session (470 once invoked), scanned A, original, no licence file.

Guidance for using GitHub, a website and service for hosting code and discussing proposed changes, through its command-line tool.

In plain words
What is it for?
It is for opening and reviewing pull requests, managing stacked pull requests, choosing merge approaches, and automating repository work.
Why use it?
It removes the need to remember detailed commands and workflows for pull requests, code reviews, branches, and repository tasks.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/aetox-skills/aetox-agents-team/github
Any agent
npx skills add aetox-skills/Aetox-Agents-Team --skill github
Clone the repo
git clone --depth 1 https://github.com/aetox-skills/Aetox-Agents-Team

Made for: Claude Code, Codex.

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 github

README.md
[![agentmods](https://agentmods.dev/badge/skills/aetox-skills/aetox-agents-team/github.svg)](https://agentmods.dev/skills/aetox-skills/aetox-agents-team/github)
Your own site
<a href="https://agentmods.dev/skills/aetox-skills/aetox-agents-team/github"><img src="https://agentmods.dev/badge/skills/aetox-skills/aetox-agents-team/github.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 470 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00043 $0.00470
Opus 5 $0.00022 $0.00235
Sonnet 5 $0.00009 $0.00094
Haiku 4.5 $0.00004 $0.00047

Measured 5d ago against content hash fdeaac730749, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github 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 5d 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.

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.

skills/github/SKILL.md · 61 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

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.

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. 5d ago First seen · 61 lines · 43 tokens per session scan A fdeaac730749

Subscribe to this mod's changes

github is a skill published in the GitHub repository aetox-skills/Aetox-Agents-Team (2 stars, last pushed 2mo ago), with no licence file. It adds 43 tokens to every session and 470 once invoked, about $0.0002 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 2026-08-31.

Related

Other skills, from other repositories

implementation-final-review

Perform the repository's risk-tiered independent final review before implementation completion. Use only when explicitly invoked or when repository instructions require it after behavior-impacting implementation work; audit the complete task diff, supported contracts, lifecycle and security boundaries, complexity, and…

openai/openai-agents-python · 58 tokens

deploy-docker-compose

Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…

omnigent-ai/omnigent · 84 tokens

api-docs

Document a module or public API surface (functions, classes, CLI commands, endpoints) from the code itself. Use when the user asks for API reference, to document a module, or to write usage docs for a public interface.

omnigent-ai/omnigent · 50 tokens

deploy-windows

Use this skill when installing, deploying, launching, serving, or troubleshooting mesh-llm on a Windows machine — PowerShell install via install.ps1, flavor selection (CUDA/ROCm/Vulkan/CPU), source builds, the contrib helper scripts, and verifying it serves.

Mesh-LLM/mesh-llm · 60 tokens

benchmark-tune

Use this skill when running, debugging, interpreting, or documenting mesh-llm benchmark tune model-serving throughput trials, including choosing ctx/batch/ubatch/mmap/mlock/speculative-decoding sweeps, running benchmark tune on local or SSH hosts, collecting JSON evidence, and applying tolerance-aware recommendations.…

Mesh-LLM/mesh-llm · 106 tokens

research

Run deep research on any topic using the Deep Research MCP server. Use this skill whenever the user wants to research a topic, gather information, find sources, or create a research document. Triggers on: 'research this', 'find out about', 'gather information on', 'I need to understand', 'deep dive into', or any…

Arindam200/awesome-ai-apps · 78 tokens