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/orkas-ai/orkas-awesome-agentskills/githubnpx skills add Orkas-AI/Orkas-Awesome-AgentSkills --skill githubgit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/github)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/github"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/github.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 5.1 | $0.00001 | $0.00579 |
| Opus 5 | $0.00000 | $0.00290 |
| Sonnet 5 | $0.00000 | $0.00116 |
| Haiku 4.5 | $0.00000 | $0.00058 |
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 6d 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.
What it actually says
GitHub
Use gh as the primary interface for GitHub data and actions. Keep this skill focused on basic operations and command safety, not maintainer triage strategy.
Before Running Commands
- Confirm
ghexists and is authenticated when live GitHub data is required. - Prefer
--repo owner/repounless the current directory is clearly inside the intended GitHub repository. - Use
--jsonand--jqwhen the result will be summarized or filtered. - Preview write actions before executing them when the user did not explicitly ask for the exact write.
- Do not close issues, merge pull requests, rerun CI, delete branches, publish releases, or edit repository settings without explicit user approval.
Common Commands
gh auth status
gh repo view --json nameWithOwner,url,defaultBranchRef
gh issue list --repo owner/repo --state open --limit 50 --json number,title,author,labels,updatedAt,url
gh issue view 123 --repo owner/repo --json number,title,author,body,comments,labels,state,url
gh pr list --repo owner/repo --state open --limit 50 --json number,title,author,isDraft,reviewDecision,mergeStateStatus,url
gh pr view 55 --repo owner/repo --json number,title,state,author,body,comments,files,commits,statusCheckRollup,url
gh pr diff 55 --repo owner/repo --patch
gh pr checks 55 --repo owner/repo
gh run list --repo owner/repo --limit 20
gh run view RUN_ID --repo owner/repo --log-failed
gh release list --repo owner/repo --limit 20
gh api repos/owner/repo/pulls/55 --jq '{title, state, user: .user.login}'
For write actions, show the intended command first and wait for approval unless the user explicitly asked for that exact action.
Default Output
When reporting GitHub data, include:
- Repository or URL inspected
- Commands or data sources used
- Current state and relevant IDs
- Any action taken, or the exact command you would run next
- Permission or authentication blockers, if any
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.
- 6d ago First seen · 48 lines · 1 tokens per session scan A 3eab60896d92
github is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 2mo ago), licensed MIT. It adds 1 tokens to every session and 579 once invoked, about $0.0000 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 2026-08-30.
Other skills, from other repositories
worktree-isolation
Worktree isolation for parallel agent execution in the pipeline.
core-workflow
Detailed development workflow patterns, checklists, and standards. Auto-loads for complex tasks, planning, debugging, testing, or when explicit patterns are needed. Contains session protocols, git conventions, security checklists, testing strategy, and communication standards.
git-worktrees
Git Worktree를 활용한 병렬 브랜치 작업 스킬.
debug-systematic
Systematic 4-phase debugging methodology for complex, intermittent, or mysterious issues. Use when investigating bugs, race conditions, or unexplained failures.
auto-claude
Autonomous multi-agent coding with git worktree isolation, QA validation, and memory. Use for complex features requiring autonomous implementation.
research-archival
Scrape AI research URLs, archive with frontmatter, create GitHub Issues with identity verification.