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Agent Skill · 待分类

skill-debugging-assistant(技能调试助手)

skill-debugging-assistant 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。

skill-debugging-assistant 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 8,476。

总安装 294周安装 12GitHub Stars 28下载 94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:skill-debugging-assistant(技能调试助手)
来源仓库:https://github.com/exploration-labs/nates-substack-skills
仓库路径:skills/skill-debugging-assistant
安装命令:
npx skills add https://github.com/exploration-labs/nates-substack-skills --skill skill-debugging-assistant
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/exploration-labs/nates-substack-skills --skill skill-debugging-assistant

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

skill-debugging-assistant 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。它能自动分析代码兼容性、依赖关系及协作流程,辅助开发决策。

可通过 npx skills add 命令从 GitHub 安装,具体用法请参考原始 README。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。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。

来源仓库内路径:skills/skill-debugging-assistant

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/exploration-labs/nates-substack-skills --skill…;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

skill-debugging-assistant 怎么安装?

在终端执行 npx skills add https://github.com/exploration-labs/nates-substack-skills --skill skill-deb…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-debugging-assistant 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。

skill-debugging-assistant 需要什么权限?

权限级别是需要联网。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。

skill-debugging-assistant 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。

skill-debugging-assistant 用的人多吗?

公开数据是累计安装 294 次,近一周安装 12 次,下载 94 次,GitHub 28 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。

skill-debugging-assistant 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
skill-debugging-assistant

技能调试助手 · 本页

29428需要联网未明确有提醒

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

Skill Debugging Assistant

Overview

This skill helps diagnose why skills aren't triggering or performing as expected. It systematically analyzes trigger patterns, parameter issues, prompt conflicts, and structural problems to identify root causes and recommend fixes.

When to Use This Skill

Use this skill when encountering any of these issues:

  • Skill doesn't trigger when expected
  • Skill triggers incorrectly or at wrong times
  • Skill behavior doesn't match description
  • Conflicts between skill instructions and system prompts
  • Unclear when to load references vs. include in SKILL.md
  • Validation errors during packaging
  • Skill works inconsistently across similar queries

Diagnostic Workflow

Follow this decision tree to diagnose skill issues:

1. Identify the Problem Type

Skill not triggering? → Go to "Trigger Failure Diagnostics"

Skill triggering incorrectly? → Go to "False Positive Diagnostics"

Skill behavior unexpected? → Go to "Instruction Conflict Diagnostics"

Packaging/validation errors? → Go to "Structure Validation"

General review needed? → Go to "Comprehensive Audit"

2. Trigger Failure Diagnostics

When a skill should trigger but doesn't, analyze in this order:

Step 1: Analyze the description field

  • Read the skill's frontmatter description
  • Check if description mentions the user's query terms or conceptual triggers
  • Verify description includes WHEN to use the skill, not just WHAT it does
  • Confirm description is specific enough to differentiate from other skills

Step 2: Check description quality

  • Does it include key terms the user would naturally use?
  • Does it specify triggers (file types, tasks, scenarios)?
  • Is it comprehensive enough for selection among 100+ skills?
  • Are the trigger scenarios clear and unambiguous?

Step 3: Review competing skills

  • Identify other skills with overlapping descriptions
  • Determine if another skill's description better matches the query
  • Check if trigger patterns are too similar between skills

Step 4: Test edge cases

  • Would the skill trigger for paraphrased versions of the query?
  • Does it cover related terminology and synonyms?
  • Are there implicit assumptions about when it should trigger?

Common fixes:

  • Add specific trigger terms to description
  • Include file type indicators (.docx,.pdf,.json)
  • Specify task types (create, edit, analyze, debug)
  • Add domain indicators (finance, legal, technical)
  • Include synonym terms users might naturally use

3. False Positive Diagnostics

When a skill triggers when it shouldn't:

Step 1: Check description over-breadth

  • Is the description too general?
  • Does it use broad terms that match many queries?
  • Are there missing qualifiers or constraints?

Step 2: Review instruction conflicts

  • Do instructions apply too broadly within SKILL.md?
  • Are there "always" or "never" statements that override context?
  • Does the skill assume it should handle something beyond its scope?

Common fixes:

  • Narrow description scope with specific qualifiers
  • Add exclusion indicators (e.g., "not for X")
  • Move broad utility functions to scripts rather than main workflow
  • Add conditional logic: "Only when..." or "If and only if..."

4. Instruction Conflict Diagnostics

When skill behavior contradicts expected results:

Step 1: Read SKILL.md completely

  • Check for absolute statements (always, never, must, required)
  • Identify instructions that might conflict with system prompt
  • Look for contradictory instructions within the skill

Step 2: Analyze instruction priority

  • Are there competing instructions without clear precedence?
  • Do examples contradict written rules?
  • Is the desired behavior stated clearly vs. implied?

Step 3: Check progressive disclosure structure

  • Is critical information buried in references that weren't loaded?
  • Should certain instructions be in SKILL.md instead of references?
  • Are references clearly indicated when they're needed?

Common fixes:

  • Replace absolutes with conditionals
  • Add explicit precedence rules
  • Move critical instructions from references to SKILL.md
  • Clarify when to load each reference file
  • Use "Prefer X, unless Y" instead of "Always X"

5. Structure Validation

Run automated and manual checks:

Automated validation:

python3 scripts/validate_skill.py path/to/skill-folder

Manual checks:

  • YAML frontmatter properly formatted (name and description present)
  • Name follows kebab-case convention
  • Description is comprehensive (>50 chars) and specific
  • SKILL.md under 500 lines (split to references if needed)
  • References clearly indicated in SKILL.md when needed
  • No extraneous files (README.md, CHANGELOG.md, etc.)
  • Assets/scripts tested and functional

Common structural issues:

  • Missing or malformed YAML frontmatter
  • Description too vague or too brief
  • SKILL.md exceeds token budget (>500 lines)
  • References not mentioned in SKILL.md
  • Unused example files not deleted
  • Scripts with syntax errors or missing dependencies

6. Comprehensive Audit

For general skill review or quality improvement:

Trigger analysis:

  1. List 5-10 queries that should trigger this skill
  2. For each query, verify the description contains relevant terms
  3. Test paraphrased versions of each query
  4. Identify gaps in trigger coverage

Instruction clarity:

  1. Read SKILL.md start to finish
  2. Flag any ambiguous or conflicting statements
  3. Verify examples align with instructions
  4. Check if workflow steps are clear and sequential

Progressive disclosure:

  1. Ensure SKILL.md contains only essential procedural knowledge
  2. Verify detailed reference material is in separate files
  3. Confirm references are clearly indicated when needed
  4. Check that SKILL.md describes when to load each reference

Quality checklist:

  • Description includes specific trigger terms and scenarios
  • SKILL.md uses imperative/infinitive form throughout
  • No conflicting instructions or absolute statements without qualifiers
  • Examples provided for non-obvious operations
  • References clearly indicated and purposefully separated
  • Scripts tested and functional
  • Token budget respected (<500 lines in SKILL.md)
  • No extraneous files included

Quick Diagnostics Checklist

For rapid troubleshooting, check these common issues first:

Trigger failures (skill not activating):

  • Description mentions user's query terms
  • Description includes "when to use" indicators
  • Description differentiates from similar skills
  • Key terms are specific, not generic

False positives (skill triggers incorrectly):

  • Description isn't too broad or generic
  • No absolute statements without context limits
  • Scope clearly defined with boundaries

Behavior issues (skill does unexpected things):

  • No conflicting "always/never" statements
  • Critical instructions in SKILL.md, not buried in references
  • Examples align with stated rules
  • Conditional logic uses "prefer" vs "always"

Validation errors:

  • YAML frontmatter properly formatted
  • Name uses kebab-case
  • Description >50 characters
  • No extraneous documentation files

Deep Analysis Methods

Description Analysis Template

For any skill with trigger issues, analyze the description systematically:

**Current description:**
[paste description here]

**Analysis:**
1. Specificity: Does it include concrete trigger terms?
2. Differentiation: How does it differ from similar skills?
3. Completeness: Does it mention when/how to use it?
4. Key terms: List the main terms that would trigger selection

**Test queries:**
[List 5 queries that should trigger this skill]
[For each, note if description contains matching terms]

**Recommended improvements:**
[Specific additions or changes to description]

Instruction Conflict Analysis

For skills with behavioral issues:

  1. Extract all imperative statements from SKILL.md
  2. Flag statements using: always, never, must, required, CRITICAL, NEVER
  3. Check each flagged statement for potential conflicts
  4. Identify statements that could override user intent
  5. Recommend conditional rephrasing

Token Budget Analysis

For skills approaching context limits:

  1. Count lines in SKILL.md (target: <500 lines)
  2. Identify sections >100 lines that could move to references
  3. Check for repetitive examples or verbose explanations
  4. Verify references are actually being used (not duplicated in SKILL.md)
  5. Recommend splits: what stays in SKILL.md vs. what moves to references

Resources

references/common-issues.md

Detailed examples of common skill problems with before/after fixes. Load this when debugging complex or recurring issues.

scripts/validate_skill.py

Automated validation script that checks:

  • YAML frontmatter format and completeness
  • File structure and naming conventions
  • Description quality metrics
  • Common structural problems

Run before packaging any skill to catch issues early.

平台分布

Codex

35.87%
按下载量换算34

Claude

29.26%
按下载量换算28

Cursor

21.55%
按下载量换算20

Gemini CLI

10.15%
按下载量换算10

安全审计

Gen Agent Trust Hub

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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