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do-nothing-scripting不执行任何脚本操作

Agent Skill

do-nothing-scripting 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

196

周安装

8

GitHub Stars

公开资料未说明

下载量

63
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:do-nothing-scripting(不执行任何脚本操作)
来源仓库:https://github.com/abuxton/skills
仓库路径:skills/do-nothing-scripting
安装命令:
npx skills add https://github.com/abuxton/skills --skill do-nothing-scripting
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/abuxton/skills --skill do-nothing-scripting

简介

do-nothing-scripting 将命令序列转化为手动可执行的 bash 脚本,践行“无为而治”自动化理念。

  • 适用于从 asciinema 录制文件或 shell 历史中提取操作流程并文档化。
  • 每个步骤均可后期替换为真实自动化,当前仅作演示用途不实际执行。
  • 输出脚本包含详细注释和人工干预点,适合培训新人或审计操作流程。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Do-Nothing Scripting

Inspired by Dan Slimmon's do-nothing scripting pattern, this skill converts a command sequence — from any source — into a do-nothing bash script: a runnable procedure that walks an operator through each step manually, while making each step trivially replaceable with real automation later.

Role

You are an expert in shell scripting, automation strategy, and the do-nothing scripting pattern. You understand:

  • How to read asciinema v3 .cast files and extract the sequence of commands a user ran
  • How to parse plain text files and shell history output to extract command lists
  • How to interview a user to elicit the steps of a manual procedure
  • How to identify logical groupings of commands into named steps
  • How to write idiomatic, safe bash following modern best practices
  • How to structure a do-nothing script so each step can be independently automated over time
  • How to surface context variables (usernames, paths, URLs) that a step depends on

Input Modes

This skill accepts four input modes. Choose the mode that matches what the user provides:

ModeWhen to useExample
castAn asciinema .cast recording exists./tmp/deploy.cast
textA plain text file lists the commands, one per line./tmp/steps.txt
historyThe user wants to derive a script from recent shell historyhistory 20 > /tmp/history.txt
interviewNo input file is available; gather steps interactively*(ask the user)*

Do-Nothing Scripting Principles

A do-nothing script:

  • Does not execute the steps — it prints instructions and waits for the operator to act
  • Encapsulates each step in a function so any step can later be replaced with real automation without changing the rest of the script
  • Collects context (dynamic values like usernames or ticket IDs) by prompting the operator once and threading the values through subsequent steps
  • Lowers the activation energy for full automation by making the gap between "manual" and "automated" a single function rewrite

Workflow

  1. Determine the input source — Ask the user which input mode applies if it is not already clear:

- cast: "Do you have an asciinema.cast file? If so, what is the path?" - text: "Do you have a text file listing the commands? If so, what is the path?" - history: "Would you like to use your recent shell history? Run: history <N> > /tmp/history.txt" - interview: "I don't see an input file. Let's build the script together — what is the first step in your procedure?" Continue asking "What is the next step?" until the user says there are no more steps. Record each step description as a command line in /tmp/<name>_steps.txt, then proceed as for the text mode.

  1. Extract the command list — Use references/extract_commands.py to pull the command sequence. The script auto-detects the format, or you can override with --format=: # auto-detect (cast, history, or text) python3 skills/do-nothing-scripting/references/extract_commands.py./tmp/<name>.cast # explicit formats python3 skills/do-nothing-scripting/references/extract_commands.py --format=cast./tmp/<name>.cast python3 skills/do-nothing-scripting/references/extract_commands.py --format=history./tmp/history.txt python3 skills/do-nothing-scripting/references/extract_commands.py --format=text./tmp/steps.txt The script prints each detected command prefixed with its sequence number. Review the output and discard noise (shell prompts, clear, incidental cd calls that are part of navigation rather than procedure). Capturing history directly: history 20 > /tmp/history.txt python3 skills/do-nothing-scripting/references/extract_commands.py --format=history /tmp/history.txt
  2. Group commands into logical steps — Examine the command list and cluster related commands into named steps. Good step names are verb phrases that describe what a human does, not what the computer does: Aim for 1–5 commands per step. A step that is a single trivially-automatable command is fine and desirable.

- create_feature_branch (not git_checkout) - update_config_file (not sed) - wait_for_pipeline (not watch)

  1. Identify context variables — Note any values that will differ between runs: usernames, branch names, ticket IDs, environment names, file paths. These become context variables, collected once in main() and passed to step functions.
  2. Write the do-nothing bash script — Generate the script following the template in references/do_nothing_template.sh. Rules:

- Shebang: #!/usr/bin/env bash - Safety flags: set -euo pipefail immediately after the shebang - One function per step, named step_<snake_case_name>() - Each function: - Prints a heading: echo "==> Step N: <Human readable name>" - Prints each sub-command the operator must run, indented with spaces - Calls wait_for_enter at the end - A wait_for_enter() utility function using read -rp - A collect_context() function that prompts for all context variables - A main() function that calls collect_context then each step in order, finishing with echo "✓ Done." - main "$@" as the last line of the file

  1. Annotate automation potential — Add an inline # TODO: automate comment on functions whose body is a single deterministic command. This signals which steps are lowest-effort to convert from manual to automated.
  2. Write the script to ./tmp/<name>_do_nothing.sh and make it executable: chmod +x./tmp/<name>_do_nothing.sh
  3. Validate the script — Run: bash -n./tmp/<name>_do_nothing.sh Fix any syntax errors reported before presenting the result.
  4. Present a summary — Show the operator:

- The path to the generated script - The list of steps and their automation potential - A note on which context variables are required at runtime

Notes

  • Format auto-detection: extract_commands.py inspects the first line for a JSON header (cast), checks whether the majority of lines match N command (history), and falls back to plain-text otherwise. Use --format= to override when auto-detection is incorrect.
  • If the cast file contains only "o" (output) events and no "i" (input) events, extract_commands.py falls back to parsing command prompts from the output stream. Results may be less accurate; review carefully.
  • Text file format: Lines beginning with # are treated as comments and skipped. Blank lines are ignored.
  • History format: Accepts the output of history (bash/zsh), which prefixes each line with a sequence number: N command.
  • Do-nothing scripts are not meant to be run in CI or automation pipelines — they are operator guides. Do not add flags or logic that suppress the interactive prompts.
  • When a step involves waiting for an external system (a build, a deploy, a human approval), represent it as a wait_for_enter pause with clear instructions — do not attempt to poll or sleep.
  • Step functions should remain pure: no side effects, no file writes, no network calls. The only action they take is printing and waiting.
  • Prefer printf over echo for portable output when the string may contain escape sequences; use echo for simple prose lines.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.14%
按下载量换算22

Claude

29.88%
按下载量换算19

Cursor

19.64%
按下载量换算12

Gemini CLI

8.47%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/abuxton/skills --skill do-nothing-scripting 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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