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comprehension-check理解力检查

Agent Skill

comprehension-check 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

269

周安装

11

GitHub Stars

24

下载量

87
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:comprehension-check(理解力检查)
来源仓库:https://github.com/noobygains/godmode
仓库路径:skills/comprehension-check
安装命令:
npx skills add https://github.com/noobygains/godmode --skill comprehension-check
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/noobygains/godmode --skill comprehension-check

简介

强制要求对 AI 生成代码有完整理解后才能提交变更。

  • 核心原则:不理解则不提交,防止认知债务累积影响后期维护。
  • 需在 PR 中清晰解释每处修改的目的与实现逻辑。comprehension-check 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 适用于重视代码可解释性、团队协作质量的中大型项目。
  • 安装前建议确认 Git 钩子配置是否允许强制执行此检查流程。

SKILL.md

Comprehension Check

Overview

AI produces code at a pace that outstrips human absorption. Shipping changes you cannot fully explain creates cognitive debt -- the inability to troubleshoot, extend, or reason about what was built.

Core principle: Comprehension precedes commitment. If you cannot articulate every modification in ordinary language, you have not earned the right to commit it.

The Prime Directive

NO COMMIT UNTIL EVERY CHANGE IS UNDERSTOOD

Before any AI-generated or AI-assisted code reaches version control, the developer must grasp what each change accomplishes and why it was implemented that way.

When to Use

Triggered after:

  • Any modification touching 3 or more files
  • Non-trivial algorithm or data-structure implementations
  • Structural shifts (new modules, altered data flow, dependency rewiring)
  • Security-adjacent code (authentication, encryption, input sanitization)
  • Autonomous agent decisions (changes you did not explicitly dictate)

Skippable for:

  • Single-character or typo corrections
  • Changes the developer dictated verbatim, line by line
  • Pure boilerplate generation (scaffolding configs, lockfiles)

The Process

Phase 1: Produce a Change Walkthrough

After implementation completes, before any commit occurs:

For EVERY modified file, articulate:

1. WHAT: What is different now? (Describe the meaning, not the diff)
2. WHY: What motivated this particular change?
3. CONTEXT: How does this change interact with the broader modification set?
4. HAZARD: What failure modes does this change introduce?

Phase 2: Deliver the Walkthrough

Structure the output as follows:

## Modification Walkthrough

### [path/to/first-file]
**What:** Introduced sliding-window rate limiting that counts requests per IP address.
**Why:** The login endpoint was exposed to brute-force enumeration.
**Context:** Middleware executes ahead of authentication routes; relies on Redis for distributed state.
**Hazard:** If Redis becomes unreachable, the limiter fails open (permits all traffic). Worth discussing: should it fail closed instead?

### [path/to/second-file]
**What:** Login handler now returns HTTP 429 when the rate limiter activates.
**Why:** The middleware flags rate-limited requests via `req.rateLimited`.
**Context:** Early exit occurs before password verification, which also blocks timing-based attacks.
**Hazard:** Negligible -- a simple conditional guard.

## Structural Consequences
- New runtime dependency: Redis (stores rate-limit counters)
- New middleware layer inserted between routing and handler execution
- Login request lifecycle now: rate-check -> authenticate -> respond

## Open Questions
1. Should the rate limiter deny all traffic when Redis is unavailable, or allow it?
2. Should rate limiting extend beyond authentication endpoints?

Phase 3: Obtain Explicit Confirmation

Ask directly: "Do you fully understand these changes and want to proceed with the commit?"

When the developer raises questions:

  • Resolve them thoroughly
  • Do not gloss over confusion
  • Lingering confusion equals accruing cognitive debt

Phase 4: Surface Unsolicited Changes

Whenever a change was not part of the original request:

HEADS UP: I additionally [modified X] because [rationale].
This was NOT part of your original instruction. Keep it or revert?

AI agents frequently make "helpful" supplementary changes. Every one must be disclosed.

Indicators of Genuine Comprehension

The developer should be able to:

  • Describe what each altered file does differently now
  • Justify why each alteration was necessary
  • Predict what would break if a specific change were rolled back
  • Enumerate any new dependencies or patterns that were introduced
  • Identify where to investigate if a bug surfaces in this code later

Cognitive Traps

RationalizationTruth
"The test suite passes, so I trust it"Tests validate behavior, not understanding. You will debug this blind later.
"I will review it when things calm down"You will not. The context window closes the moment you move on.
"It is mostly boilerplate"A single incorrect line in boilerplate can open a security hole.
"I grasp the overall concept"High-level intuition collapses at debugging time. Specific comprehension is required.
"Deep review reduces my velocity"Deploying code you cannot explain reduces velocity far more when it fails.
"The AI is competent"AI generates plausible output. Plausible and correct are not the same thing.

Guardrails

Prohibited actions:

  • Committing AI-produced code without reading the walkthrough
  • Suppressing unsolicited-change disclosures
  • Rushing past developer confusion or uncertainty
  • Equating green tests with genuine comprehension

Required actions:

  • Generate walkthroughs for all multi-file modifications
  • Disclose every change that exceeded the original request
  • Collect explicit confirmation before committing
  • Fully resolve every developer question

Integration

Invoked after:

  • godmode:delegated-execution -- Review output from delegated agent implementations
  • godmode:test-first -- After code is written and tests pass
  • godmode:parallel-execution -- After merging results from parallel agent work

Invoked before:

  • godmode:completion-gate -- First understand, then verify
  • godmode:merge-protocol -- Understand before merging into the target branch

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

34.82%
按下载量换算30

Claude

31.83%
按下载量换算28

Cursor

19.31%
按下载量换算17

Gemini CLI

9.13%
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

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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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