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/misonl/ling/bash-linuxnpx skills add MisonL/Ling --skill bash-linuxgit clone --depth 1 https://github.com/MisonL/LingWhat 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 | $0.00057 | $0.01781 |
| Opus 5 | $0.00028 | $0.00890 |
| Sonnet 5 | $0.00011 | $0.00356 |
| Haiku 4.5 | $0.00006 | $0.00178 |
Grade B, and why
bash-linux scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
| POST JSON（发送 JSON） | `curl -X POST -H "Content-Type: application/json" -d '{"key":"value"}' URL` | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Download（下载） | `curl -O https://example.com/file` | This is a copy
84% identical to bash-linux — 184 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bash Linux Patterns（Bash/Linux 实践模式）
Essential patterns for Bash on Linux/macOS（适用于 Linux/macOS 的 Bash 核心模式）。
1. Operator Syntax（操作符语法）
Chaining Commands（链式命令）
| Operator（操作符） | Meaning（含义） | Example（示例） |
|---|---|---|
; |
Run sequentially（顺序执行） | cmd1; cmd2 |
&& |
Run if previous succeeded（前一命令成功后执行） | npm install && npm run dev |
| ` | ` | |
| ` | ` | Pipe output（管道输出） |
2. File Operations（文件操作）
Essential Commands（核心命令）
| Task（任务） | Command（命令） |
|---|---|
| List all（列出所有） | ls -la |
| Find files（查找文件） | find . -name "*.js" -type f |
| File content（查看内容） | cat file.txt |
| First N lines（前 N 行） | head -n 20 file.txt |
| Last N lines（后 N 行） | tail -n 20 file.txt |
| Follow log（跟踪日志） | tail -f log.txt |
| Search in files（文件内搜索） | grep -r "pattern" --include="*.js" |
| File size（文件大小） | du -sh * |
| Disk usage（磁盘占用） | df -h |
3. Process Management（进程管理）
| Task（任务） | Command（命令） |
|---|---|
| List processes（列出进程） | ps aux |
| Find by name（按名查找） | `ps aux |
| Kill by PID（按 PID 终止） | kill -9 <PID> |
| Find port user（查占用端口） | lsof -i :3000 |
| Kill port（释放端口） | kill -9 $(lsof -t -i :3000) |
| Background（后台运行） | npm run dev & |
| Jobs（作业列表） | jobs -l |
| Bring to front（切回前台） | fg %1 |
4. Text Processing（文本处理）
Core Tools（核心工具）
| Tool（工具） | Purpose（用途） | Example（示例） |
|---|---|---|
grep |
Search（搜索） | grep -rn "TODO" src/ |
sed |
Replace（替换） | sed -i 's/old/new/g' file.txt |
awk |
Extract columns（列提取） | awk '{print $1}' file.txt |
cut |
Cut fields（字段切割） | cut -d',' -f1 data.csv |
sort |
Sort lines（排序） | sort -u file.txt |
uniq |
Unique lines（去重） | `sort file.txt |
wc |
Count（计数） | wc -l file.txt |
5. Environment Variables（环境变量）
| Task（任务） | Command（命令） |
|---|---|
| View all（查看全部） | env or printenv |
| View one（查看单个） | echo $PATH |
| Set temporary（临时设置） | export VAR="value" |
| Set in script（命令内设置） | VAR="value" command |
| Add to PATH（追加 PATH） | export PATH="$PATH:/new/path" |
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.
- yesterday First seen · 202 lines · 57 tokens per session scan B 32929387b9e2
bash-linux is a skill published in the GitHub repository MisonL/Ling (9 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 1,781 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 84% identical to bash-linux, differing in 184 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…