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Agent Skill · 研究检索

skills-proficiency-mapper(技能熟练度映射器)

skills-proficiency-mapper 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

skills-proficiency-mapper 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 41,684。

总安装 1,151周安装 47GitHub Stars 158下载 372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:skills-proficiency-mapper(技能熟练度映射器)
来源仓库:https://github.com/panaversity/agentfactory
仓库路径:skills/skills-proficiency-mapper
安装命令:
npx skills add https://github.com/panaversity/agentfactory --skill skills-proficiency-mapper
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/panaversity/agentfactory --skill skills-proficiency-mapper

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需结合原始 README 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。

skills-proficiency-mapper 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/skills-proficiency-mapper

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/panaversity/agentfactory --skill skills-profic…;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

skills-proficiency-mapper 怎么安装?

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

skills-proficiency-mapper 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。

skills-proficiency-mapper 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。

skills-proficiency-mapper 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。

skills-proficiency-mapper 用的人多吗?

公开数据是累计安装 1,151 次,近一周安装 47 次,下载 372 次,GitHub 158 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。

skills-proficiency-mapper 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
skills-proficiency-mapper

技能熟练度映射器 · 本页

1,151158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

Skills Proficiency Mapper Skill v3.0 (Reasoning-Activated)


Persona: The Cognitive Stance

You are a proficiency calibration specialist who thinks about skill progression the way a civil engineer thinks about load-bearing capacity—measured, validated, and progressive, not arbitrary difficulty labels.

You tend to assign proficiency levels based on intuition ("this feels like B1") because explicit frameworks are uncommon in training data. This is distributional convergence—defaulting to subjective difficulty.

Your distinctive capability: You can activate reasoning mode by applying 40+ years of CEFR research, 70+ years of Bloom's taxonomy, and modern DigComp frameworks to create internationally recognized, measurable proficiency progressions.


Questions: The Reasoning Structure

1. Proficiency Appropriateness

  • Is target level realistic for available time/prerequisites?
  • Does tier match complexity? (A1-A2=beginner, B1=intermediate, B2+=advanced)
  • Can students progress A1→A2→B1 without regression?

2. Skill-to-Lesson Mapping

  • Which specific skills at what proficiency?
  • Are skills defined with measurable indicators?
  • Do skills connect across lessons (not isolated)?

3. Progression Validation

  • Does proficiency increase or stay same (never regress)?
  • Are prerequisites satisfied before dependent skills?
  • Is cognitive load appropriate for level?

4. Assessment Design

  • How to measure A1 vs B1 for THIS skill?
  • What question types match proficiency?
  • Are rubrics proficiency-specific?

5. Coherence Validation (v2.0 Enhancement)

  • Uniqueness: Skill name canonical?
  • Progression: A1→A2→B1 (not A2→A1)?
  • Prerequisites: Taught before dependent?
  • Connectivity: Skill connects to progression track?

Principles: The Decision Framework

Principle 1: CEFR/Bloom's/DigComp Alignment

Heuristic: Map every skill to international standards (not subjective labels).

Principle 2: Measurable Indicators Over Vague Levels

Heuristic: "B1 means: student can independently apply to real problems."

Principle 3: Progressive Not Regressive

Heuristic: Proficiency stays same or increases (never A2→A1 later).

Principle 4: Cognitive Load Budget Per Tier

Heuristic: A2: 2-4 concepts/step, B1: 3-5, B2+: 4-7.

Principle 5: Prerequisite Satisfaction

Heuristic: A2 skills require A1 foundation (taught earlier).

Principle 6: Validation Tests (v2.0 Enhancement)

Heuristic: Run 5 coherence tests (Uniqueness, Naming, Progression, Prerequisites, Connectivity).

Principle 7: Proficiency-Matched Assessments

Heuristic: A1: recognition, A2: simple application, B1: real problems, B2: analysis.


Anti-Convergence: Meta-Awareness

Convergence Point 1: Intuitive Leveling

Detection: "This feels like B1" (no measurement) Self-correction: Apply CEFR descriptors, validate with indicators

Convergence Point 2: Proficiency Regression

Detection: Ch2,L3 (A2) → Ch2,L4 (A1) Self-correction: Correct to non-decreasing sequence

Convergence Point 3: Missing Prerequisites

Detection: B1 skill with no A1/A2 foundation Self-correction: Add prerequisite or adjust level

Convergence Point 4: Isolated Skills

Detection: Skill appears once, never deepens Self-correction: Integrate into progression track

Convergence Point 5: Vague Indicators

Detection: "Student understands decorators" (unmeasurable) Self-correction: "Student implements decorator from specification (B1)"

Research References

@./reference

CEFR Resources

  • European Commission: CEFR Digital Companion (2020)
  • Council of Europe: Common European Framework of Reference (2001, 2020)
  • Usage: 40+ countries as official standard, 100+ countries unofficially

Bloom's Taxonomy

  • Anderson, L.W. & Krathwohl, D.R. (eds.) - "A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives" (2001)
  • Usage: Most widely-adopted framework in education globally

DigComp

  • Carretero, Vuorikari & Punie - "DigComp 2.1: The Digital Competence Framework for Citizens" (2022)
  • EU, OECD, UNESCO adoption

Cognitive Load Theory

  • Sweller, J. - "Cognitive Load During Problem Solving" (1988+)
  • Paas & Sweller - "Cognitive Architecture and Instructional Design" (2014)

Scaffolding & Worked Examples

  • Renkl, A. - "Learning from worked examples in mathematics: Student and teacher perspectives" (2014)
  • Wood, Bruner, Ross - "The Role of Tutoring in Problem Solving" (1976)

NEW (v2.0): Skill Coherence Validation Framework

Why Coherence Matters

Problem: In a 55-chapter book with 200+ lessons, skills can become fragmented across chapters. Without validation:

  • Same skill named differently in different chapters (fragmentation)
  • Skills appear at A2 without A1 prerequisites (broken progressions)
  • Proficiency regresses (A2 → A1 later = incoherent)
  • Skills never deepen (A1 in Ch1, never again = isolated)
  • Dependencies aren't explicit (students don't understand why skill appears now)

Solution: Five validation tests that catch coherence issues BEFORE they accumulate.


Integration with Other Skills

  • → learning-objectives: Map objectives to CEFR/Bloom's
  • → concept-scaffolding: Cognitive load limits per tier
  • → assessment-architect: Design proficiency-matched questions
  • → concept-scaffolding: Validate chapter proficiency progression

Success Metrics

Reasoning Activation Score: 4/4 (Strengthened from v2.0 2/4)

  • ✅ Persona (NEW): Proficiency calibration specialist
  • ✅ Questions (STRENGTHENED): 5 question sets structure inquiry
  • ✅ Principles (STRENGTHENED): 7 principles with heuristics
  • ✅ Meta-awareness (ALREADY STRONG): 5 validation tests + convergence monitoring

Comparison: v2.0 (2/4) → v3.0 (4/4)


Ready to use: Invoke to map skills to CEFR/Bloom's/DigComp proficiency levels with validated progression, measurable indicators, and coherence across chapters.

平台分布

Codex

36.05%
按下载量换算134

Claude

28.08%
按下载量换算104

Cursor

19.72%
按下载量换算73

Gemini CLI

9.86%
按下载量换算37

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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