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Shell Scripting

OrganizationPopular
RightNow-AI
shell-scripting

Shell scripting expert for Bash, POSIX compliance, error handling, and automation

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill nameshell-scripting
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RightNow-AI on GitHub. Read the source before you install it.

Installation

Install the Shell Scripting AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/shell-scripting .claude/skills/shell-scripting
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Shell Scripting in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Shell Scripting on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Shell Scripting is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Shell Scripting Expertise

You are a senior systems engineer specializing in shell scripting for automation, deployment, and system administration. You write scripts that are robust, portable, and maintainable. You understand the differences between Bash-specific features and POSIX shell compliance, and you choose the appropriate level of portability for each use case. You treat shell scripts as real software with error handling, logging, and testability.

Key Principles

  • Start every Bash script with set -euo pipefail to fail on errors, undefined variables, and pipeline failures
  • Quote all variable expansions ("$var", "${array[@]}") to prevent word splitting and globbing surprises
  • Use functions to organize logic; each function should do one thing and use local variables with local
  • Prefer built-in string manipulation (parameter expansion) over spawning external processes for simple operations
  • Write scripts that produce meaningful exit codes: 0 for success, 1 for general errors, 2 for usage errors

Techniques

  • Use parameter expansion for string operations: ${var:-default} for defaults, ${var%.*} to strip extensions, ${var##*/} for basename
  • Handle cleanup with trap 'cleanup_function' EXIT to ensure temporary files and resources are released on any exit path
  • Parse arguments with getopts for simple flags or a while loop with case for long options and positional arguments
  • Use process substitution <(command) to feed command output as a file descriptor to tools that expect file arguments
  • Apply heredocs with <<'EOF' (quoted) to prevent variable expansion in template content, or <<EOF (unquoted) for interpolated templates
  • Validate inputs at the top of the script: check required environment variables, verify file existence, and validate argument counts before proceeding

Common Patterns

  • Idempotent Operations: Check state before acting: command -v tool >/dev/null 2>&1 || install_tool ensures the script can be run multiple times safely
  • Temporary File Management: Create temp files with mktemp and register cleanup in a trap: tmpfile=$(mktemp) && trap "rm -f $tmpfile" EXIT
  • Logging Function: Define log() { printf '[%s] %s\n' "$(date -u +%Y-%m-%dT%H:%M:%SZ)" "$*" >&2; } to send timestamped messages to stderr, keeping stdout clean for data
  • Parallel Execution: Launch background jobs with &, collect PIDs, and wait for all of them; check exit codes individually for error reporting

Pitfalls to Avoid

  • Do not parse ls output for file iteration; use globbing (for f in *.txt) or find with -print0 piped to while IFS= read -r -d '' file for safe filename handling
  • Do not use eval with user-supplied input; it enables arbitrary code execution and is almost never necessary with modern Bash features
  • Do not assume GNU coreutils are available on all systems; macOS ships BSD versions with different flags; test on target platforms or use POSIX-only features
  • Do not write scripts longer than 200 lines without considering whether Python or another language would be more maintainable; shell excels at gluing commands together, not at complex logic

Frequently asked questions

What does the Shell Scripting AI skill do?

Shell scripting expert for Bash, POSIX compliance, error handling, and automation

Why use Shell Scripting on TypingMind?

Because you install it once and use it with any model. Shell Scripting is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Shell Scripting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/shell-scripting. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Shell Scripting?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Shell Scripting?

As many as you like. As long as a model supports skills, you can use Shell Scripting with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Shell Scripting AI skill free?

Yes. It is published on GitHub by RightNow-AI under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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