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 russodope/ai-cli-kit --skill ai-command-rulesgit clone --depth 1 https://github.com/russodope/ai-cli-kitWrote 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/russodope/ai-cli-kit/ai-command-rules)<a href="https://agentmods.dev/skills/russodope/ai-cli-kit/ai-command-rules"><img src="https://agentmods.dev/badge/skills/russodope/ai-cli-kit/ai-command-rules/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/russodope/ai-cli-kit/ai-command-rules"><img src="https://agentmods.dev/badge/skills/russodope/ai-cli-kit/ai-command-rules.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 | $0.00151 | $0.01785 |
| Opus 5.5 | $0.00060 | $0.00714 |
| Sonnet 5.5 | $0.00030 | $0.00357 |
| Haiku 4.5 | $0.00015 | $0.00178 |
Grade D, and why
ai-command-rules scanned grade D with 3 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 2mo 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
| Privileges | Root/sudo available? Admin on Windows? | Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| `rm -rf dist/` | `rm -rf ./dist/` | Protects against accidental root deletion | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
5. **Network** — check if egress is allowed before running `curl`, `pip install`, `npm install` How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Command Rules
A skill for writing precise, environment-aware shell commands and scripts that work correctly the first time across Windows, Linux, macOS, sandboxes, virtual environments, and containers.
Core Principle
Always detect the environment before writing a command. Never assume. A command that works on Linux bash will silently fail or behave differently on Windows CMD, PowerShell, or macOS zsh. When in doubt, ask or emit environment-adaptive commands.
Step 1: Detect the Environment
Before writing any command, identify:
| Signal | How to detect |
|---|---|
| OS | User mentions, file paths (C:\ vs /), or ask explicitly |
| Shell | bash / zsh / fish / PowerShell / CMD / sh |
| Runtime context | Local terminal, Docker container, CI/CD, sandbox, SSH session |
| Python env | venv, conda, pipenv, poetry, system Python, Docker |
| Privileges | Root/sudo available? Admin on Windows? |
If uncertain, emit a detection snippet first:
# Universal OS+shell detector (paste in terminal first)
echo "OS: $(uname -s 2>/dev/null || echo Windows)"
echo "Shell: $SHELL"
echo "Python: $(python --version 2>&1 || python3 --version 2>&1)"
Step 2: Environment-Specific Rules
Read the relevant reference file before emitting commands:
- Linux / macOS / bash / zsh →
references/unix.md - Windows CMD / PowerShell / WSL →
references/windows.md - Docker / containers / sandboxes →
references/containers.md - Python / virtual environments →
references/python-env.md - SSH / remote execution →
references/ssh-remote.md - Git →
references/git.md
For cross-platform tasks, read all relevant files.
Step 3: Command Writing Checklist
Before emitting any command block, verify:
✅ Shell Compatibility
- Correct quoting style for target shell (single vs double vs backtick)
- Path separator correct (
/vs\) - Line continuation correct (
\bash vs`PowerShell) - Variable syntax correct (
$VARbash vs$env:VARPowerShell vs%VAR%CMD) - Logical operators correct (
&&/||bash vs-and/-orPowerShell)
What ships with it
6 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.
- 2mo ago First seen · 178 lines · 151 tokens per session scan D 1577355f3cf0
ai-command-rules is a skill published in the GitHub repository russodope/ai-cli-kit (2 stars, last pushed 8mo ago), licensed MIT. It adds 151 tokens to every session and 1,785 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it D with 3 findings (asks for root, recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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