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 skills add yunze7373/openclaw-termux --skill githubgit clone --depth 1 https://github.com/yunze7373/openclaw-termuxWrote 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/yunze7373/openclaw-termux/github)<a href="https://agentmods.dev/skills/yunze7373/openclaw-termux/github"><img src="https://agentmods.dev/badge/skills/yunze7373/openclaw-termux/github/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yunze7373/openclaw-termux/github"><img src="https://agentmods.dev/badge/skills/yunze7373/openclaw-termux/github.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00101 | $0.01139 |
| Opus 5.5 | $0.00040 | $0.00456 |
| Sonnet 5.5 | $0.00020 | $0.00228 |
| Haiku 4.5 | $0.00010 | $0.00114 |
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 1mo 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.
This is a copy
88% identical to github — 2 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Skill
Use the gh CLI to interact with GitHub repositories, issues, PRs, and CI.
When to Use
✅ USE this skill when:
- Checking PR status, reviews, or merge readiness
- Viewing CI/workflow run status and logs
- Creating, closing, or commenting on issues
- Creating or merging pull requests
- Querying GitHub API for repository data
- Listing repos, releases, or collaborators
When NOT to Use
❌ DON'T use this skill when:
- Local git operations (commit, push, pull, branch) → use
gitdirectly - Non-GitHub repos (GitLab, Bitbucket, self-hosted) → different CLIs
- Cloning repositories → use
git clone - Reviewing actual code changes → use
coding-agentskill - Complex multi-file diffs → use
coding-agentor read files directly
Setup
# Authenticate (one-time)
gh auth login
# Verify
gh auth status
Common Commands
Pull Requests
# List PRs
gh pr list --repo owner/repo
# Check CI status
gh pr checks 55 --repo owner/repo
# View PR details
gh pr view 55 --repo owner/repo
# Create PR
gh pr create --title "feat: add feature" --body "Description"
# Merge PR
gh pr merge 55 --squash --repo owner/repo
Issues
# List issues
gh issue list --repo owner/repo --state open
# Create issue
gh issue create --title "Bug: something broken" --body "Details..."
# Close issue
gh issue close 42 --repo owner/repo
CI/Workflow Runs
# List recent runs
gh run list --repo owner/repo --limit 10
# View specific run
gh run view <run-id> --repo owner/repo
# View failed step logs only
gh run view <run-id> --repo owner/repo --log-failed
# Re-run failed jobs
gh run rerun <run-id> --failed --repo owner/repo
API Queries
# Get PR with specific fields
gh api repos/owner/repo/pulls/55 --jq '.title, .state, .user.login'
# List all labels
gh api repos/owner/repo/labels --jq '.[].name'
# Get repo stats
gh api repos/owner/repo --jq '{stars: .stargazers_count, forks: .forks_count}'
JSON Output
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.
- 1mo ago First seen · 164 lines · 101 tokens per session scan A 40c016d16a14
github is a skill published in the GitHub repository yunze7373/openclaw-termux (2 stars, last pushed 3mo ago), licensed MIT. It adds 101 tokens to every session and 1,139 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to github, differing in 2 lines, and is treated as a copy.
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engineer-bot-getting-started
An onboarding guide for an engineering delivery assistant. It helps define a repository, the allowed level of access, and the work needed before reviewing a code change.
engineer-bot-ops
A workflow for carrying an engineering task from scope through implementation and reviewable delivery. It works with a repository's branch, existing changes, rules, checks, and permissions while separating completed, unverified, and next-step work.
nightly-audit-engineer-getting-started
A first-conversation guide for setting up a code-audit assistant. A code audit is a focused review of source code for defects or risky behavior, with the needed repository, scope, concerns, permissions, and schedule clarified first.
nightly-audit-engineer-ops
A workflow for reviewing code for reproducible quality problems and recording the evidence behind each finding. It follows data through inputs, permissions, storage, asynchronous work, and recovery, then suggests the smallest authorized fix.
nightly-audit-engineer-evidence
A small local checker that creates stable identifiers for code-audit findings and marks duplicates within the current batch or among previously seen findings. It processes supplied JSON with Python and does not infer whether a problem was fixed.
engineer-bot-evidence
A local checker for confirming that delivery checks and supporting evidence belong to the current software version. It does not contact Git, continuous-integration systems, or the internet.