github

A set of instructions for using the GitHub command-line tool, which lets developers work with repositories from a terminal. It covers pull requests, issues, automated checks, workflow runs, and advanced GitHub data.

In plain words
What is it for?
Use it to check pull-request checks, list or inspect CI workflow runs, manage issues, and make structured GitHub API queries.
Why use it?
It provides the command patterns needed to inspect and query GitHub without relying on a web interface.

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/render-examples/nanobot-render/github
Any agent
npx skills add render-examples/nanobot-render --skill github
Clone the repo
git clone --depth 1 https://github.com/render-examples/nanobot-render

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 387 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00044 $0.00387
Opus 5 $0.00022 $0.00193
Sonnet 5 $0.00009 $0.00077
Haiku 4.5 $0.00004 $0.00039

Measured yesterday against content hash bd1c4b4acec5, 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 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

This is a copy

100% identical to github — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

nanobot/skills/github/SKILL.md · 49 lines

What it actually says

GitHub Skill

Use the gh CLI to interact with GitHub. Always specify --repo owner/repo when not in a git directory, or use URLs directly.

Pull Requests

Check CI status on a PR:

gh pr checks 55 --repo owner/repo

List recent workflow runs:

gh run list --repo owner/repo --limit 10

View a run and see which steps failed:

gh run view <run-id> --repo owner/repo

View logs for failed steps only:

gh run view <run-id> --repo owner/repo --log-failed

API for Advanced Queries

The gh api command is useful for accessing data not available through other subcommands.

Get PR with specific fields:

gh api repos/owner/repo/pulls/55 --jq '.title, .state, .user.login'

JSON Output

Most commands support --json for structured output. You can use --jq to filter:

gh issue list --repo owner/repo --json number,title --jq '.[] | "\(.number): \(.title)"'
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 · 49 lines · 44 tokens per session scan A bd1c4b4acec5

Subscribe to this mod's changes

github is a skill published in the GitHub repository render-examples/nanobot-render (5 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 387 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to github, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

lumina-backend-api

Implement and debug the Express and TypeScript backend for Lumina. Use when editing files under server/src or server/package.json, changing authentication, conversations, guest flows, chat routes, models, middleware, API contracts, or Gemini and Pinecone service wiring outside the dedicated knowledge-ingestion…

hoangsonww/AI-RAG-Assistant-Chatbot · 64 tokens

lumina-frontend-ui

Build, refine, and debug the React/Vite frontend for Lumina. Use when editing files under client/src or client/package.json, changing chat UX, landing page content, auth flows, routing, theme behavior, markdown rendering, animations, responsive layout, or frontend API wiring.

hoangsonww/AI-RAG-Assistant-Chatbot · 62 tokens

lumina-mcp-server

Develop and maintain the standalone Lumina MCP server. Use when editing files under mcpserver/, adding or modifying tools, resources, prompts, middleware, configuration, or transport behavior for the Model Context Protocol server.

hoangsonww/AI-RAG-Assistant-Chatbot · 48 tokens

lumina-rag-knowledge

Manage Lumina's retrieval-augmented generation and knowledge ingestion workflow. Use when editing server/src/services/knowledgeBase.ts, server/src/services/pineconeClient.ts, server/src/scripts/knowledgeCli.ts, server/src/models/KnowledgeSource.ts, files under server/knowledge, manifest-based sync inputs, or debugging…

hoangsonww/AI-RAG-Assistant-Chatbot · 83 tokens

lumina-agentic-mcp

Work on the Python multi-agent pipeline and MCP client in agenticai. Use when editing files under agenticai/, changing agent orchestration, configuration loading, MCP client connectivity, async execution flow, pipeline startup commands, or cloud deployment wrappers for the Python service.

hoangsonww/AI-RAG-Assistant-Chatbot · 60 tokens

lumina-infra-deploy

Work on Lumina deployment and infrastructure assets. Use when editing terraform/, aws/, docker-compose.yml, DEPLOYMENT.md, ADVANCEDDEPLOYMENTS.md, agenticai/deployments/, or other files related to Docker, Terraform, AWS or Azure rollout behavior, environment wiring, and release automation.

hoangsonww/AI-RAG-Assistant-Chatbot · 68 tokens