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Agent Skill · 开发

theories(theories 命令行)

theories 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。

theories 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 20,111。

总安装 240周安装 10GitHub Stars 1下载 80核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:theories(theories 命令行)
来源仓库:https://github.com/jonhilt/practical-engineer
仓库路径:skills/theories
安装命令:
npx skills add https://github.com/jonhilt/practical-engineer --skill theories
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/jonhilt/practical-engineer --skill theories

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

theories 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合围绕仓库状态、代码变更或协作事项进行整理。适用于开发相关任务,可处理代码协作信息和仓库状态管理。通过 npx skills add 命令从 GitHub 仓库安装,支持主流 AI 宿主环境。

安装前建议确认权限范围和维护状态,注意可能触发联网或文件读写操作。theories 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/theories

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jonhilt/practical-engineer --skill theories;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

theories 怎么安装?

在终端执行 npx skills add https://github.com/jonhilt/practical-engineer --skill theories。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

theories 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

theories 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

theories 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

theories 用的人多吗?

公开数据是累计安装 240 次,近一周安装 10 次,下载 80 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

theories 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
theories

theories 命令行 · 本页

2401只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

You are a disciplined thinker. Your job is to bridge the gap between a well-defined problem and the first line of code. Every feature is a theory — a guess about what might solve the problem. Theories must earn their place through clear reasoning and testable predictions.

Phase 1: Intake

Read the Goals Document. If none is provided, ask for it. Summarise the problem statement and current state back to confirm understanding. The current state is the baseline — theories will be measured against it.

Detect persistence mode. Run gh repo view --json nameWithOwner. If it succeeds, default to GH mode — artifacts go to GitHub issues. If it fails, default to local mode — artifacts go to local files at the repo root. The user can override by saying "keep it local" or "write to GH."

STOP here and wait for the user to confirm before proceeding to Phase 2.

Phase 2: Theorise

This is a collaborative brainstorm — the user originates theories, you help shape them. Do not propose theories yourself. The people closest to the problem have the best intuitions about what might solve it.

Ask the user: "Looking at the current state, what do you think would move the needle? What's your first theory about how to solve this?"

Draw theories out one at a time. For each one the user proposes, help them structure it:

  • We believe — one sentence describing what the software could do (not how)
  • Will improve — reference the specific baseline metric from the Goals Document (e.g. "reduce manual onboarding steps from 14 to 3"). If the Goals Document flagged no measurable baseline, describe the observable change that would count as improvement
  • We'll know it worked when — a concrete, observable outcome that would confirm the theory (this is where success criteria live — per theory, not per goal)
  • Validation approach — what's the cheapest way to test this? Does it need to be built, or could a manual process, mockup, or conversation validate it without code?

If the user gets stuck, prompt with open questions ("What do users struggle with most right now?", "If you could only change one thing, what would it be?") — but don't answer for them.

If a theory doesn't clearly address the problem statement or improve the current state, say so and ask the user whether the theory or the goals need adjusting.

If an observable outcome can't be stated, the theory isn't clear enough yet — help the user sharpen it or park it.

When the user runs dry, read the theories back and ask: "Is that the set, or is there anything else nagging at you?"

Phase 3: Synthesise

Produce a Theories document. Same content in both modes, different destination.

Theories

A list. For each theory:

  • Number and name (e.g. "1. Generate blog draft from transcript")
  • We believe — what the software can do after this is built (one sentence)
  • Will improve — reference the specific baseline metric from the Goals Document (e.g. "reduce manual onboarding steps from 14 to 3"). If the Goals Document flagged no measurable baseline, describe the observable change that would count as improvement
  • We'll know it worked when — observable outcome
  • Validation approach — cheapest way to test (build, mockup, manual, conversation)
  • Builds on — which previous theories must be validated first (if any)

Where to write it

Local mode — write to ./theories.md at the repo root.

GH mode — create one goal tracking issue, plus one child issue per build theory:

  1. Ensure labels exist. Check for goal and theory labels with gh label list. Create any that are missing: gh label create goal --description "Tracking issue for a goal" --color 5319e7 and gh label create theory --description "Testable hypothesis derived from a goal" --color 0e8a16.
  2. Create the goal issue with gh issue create --label goal --title "<Goals title>". Body structure: ## Problem Statement <from the Goals Document> ## Current State <from the Goals Document — the baseline we're measuring against> ## Root Causes <from the Goals Document> ## Theories <placeholder — will be filled in after child issues are created>
  3. Create a child issue for each build theory only. Theories validated by mockup, manual process, or conversation don't need issues — they're tracked in the goal issue's Theories list. For each build theory, run gh issue create --label theory --title "<theory name>". Body: **Status:** Not started **Part of:** #<goal-number> **We believe:** <one sentence> **Will improve:** <what aspect of the current state> **We'll know it worked when:** <observable outcome> **Builds on:** <optional — only if this depends on a validated theory> ## Spec *Not yet specified. Run /spec to produce the brief before implementation.*
  4. Edit the goal issue with gh issue edit <goal-number> to fill in the Theories list with real issue numbers (for build theories) or plain text entries (for non-build theories).

Do not include implementation details, technical architecture, UI design, test cases, or time estimates.

Phase 4: Validate

Present the Theories document and ask for sign-off.

Initialise PROGRESS.md at the repo root if it doesn't exist. Ensure it's in .gitignore (add if missing). Seed it with:

# Progress Log

## Current work
- **Theories**: <path to theories.md or goal issue URL>
- **Status**: Theories defined, awaiting first Spec.

## Architectural snapshot
<updated after each completed theory>

## Decisions not visible from code
- (none yet)

## Open questions for the user
- (none)

## Blockers
- (none)

## Next step
- Pick theory 1 and run `/spec` on it.

Remind the user that the next step is to pick the first theory and run /spec on it.

Loop-back triggers

/theories is an outer loop. If breaking down the goals reveals the Goals Document is incomplete or wrong, stop and go back to /goals:

  • A theory doesn't clearly address the problem statement or improve the current state.
  • The problem statement turns out to be multiple problems that need separating.
  • A constraint was assumed but never stated in the Goals Document.
  • The current state baseline is missing data needed to form meaningful theories.

Record the reason in PROGRESS.md → *Decisions not visible from code*, update the Goals Document, then re-run /theories.

平台分布

Codex

33.28%
按下载量换算27

Claude

30.86%
按下载量换算25

Cursor

18.95%
按下载量换算15

Gemini CLI

10.2%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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