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Agent Skill · 研究检索

competency-builder(能力建设者)

competency-builder 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。

competency-builder 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;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 19,467。

总安装 5,598周安装 238GitHub Stars 69下载 1,961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
MIT

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:competency-builder(能力建设者)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/competency-builder
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill competency-builder
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill competency-builder

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,支持能力建设诊断。适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否触发联网或文件读写。

competency-builder 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/competency-builder

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/jwynia/agent-skills --skill competency-builder;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

competency-builder 怎么安装?

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

competency-builder 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。

competency-builder 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。

competency-builder 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

competency-builder 用的人多吗?

公开数据是累计安装 5,598 次,近一周安装 238 次,下载 1,961 次,GitHub 69 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。

competency-builder 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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
competency-builder

能力建设者 · 本页

5,59869只读MIT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

Competency Builder Skill

Build and operate competency frameworks that produce capability—not just completion. Diagnose where competency development is stuck and guide the next step.

Core Principle

Competencies are observable capabilities, not knowledge states. If you can't watch someone demonstrate it, it's not a competency.


Diagnostic States

CF0: No Framework

Symptoms: Have training content but no competency structure. People complete training but can't apply it. Same questions keep getting asked.

Test:

  • What decisions do people need to make with this knowledge?
  • What mistakes indicate someone lacks competency?
  • Can you describe what a competent person can DO?

Intervention: Start with failure modes. List mistakes you've seen, questions that shouldn't need asking, things that take too long. Each failure mode suggests a competency that would prevent it.


CF1: Content-First Trap

Symptoms: Started by listing all the information people need to know. Training is comprehensive but competence is low. "We trained on that" but mistakes continue.

Test:

  • Can you describe what someone with this competency can DO?
  • What would you watch them do to verify competency?
  • Does each content piece connect to a specific competency?

Intervention: Reframe each content chunk as "what decision/action does this enable?" Kill orphan content that doesn't support a competency. Work backward from actions to required knowledge.


CF2: Vague Competencies

Symptoms: Competencies are knowledge states ("understands X") not capabilities ("can evaluate X against Y"). Can't tell if someone has the competency or not.

Test:

  • Could two people disagree about whether someone has this competency?
  • Can you observe it?
  • Does it start with "Can" + action verb?

Intervention: Rewrite each competency as observable behavior. Transform:

  • "Understands data policies" → "Can classify data according to policy categories"
  • "Knows the approval process" → "Can determine required approval level for a given case"
  • "Familiar with the tool" → "Can configure the tool to accomplish [specific task]"

CF3: No Scenarios

Symptoms: Competencies defined but no way to test them. Assessment is knowledge recall (quizzes, multiple choice). People pass but fail in real situations.

Test:

  • What realistic situation requires this competency?
  • Does assessment require judgment, or can it be answered by searching documentation?
  • What would a weak vs. strong response look like?

Intervention: For each core competency, create a scenario that:

  1. Presents a realistic situation
  2. Includes incomplete information
  3. Requires judgment (not just recall)
  4. Has better and worse responses (not binary right/wrong)

Create variants: interview (generic), assessment (org-specific), ongoing (real situations).


CF4: Simple Scenarios

Symptoms: Scenarios exist but have artificial clarity. All information needed is provided. There's an obvious "right answer." People pass but fail in messy real situations.

Test:

  • Do scenarios match the ambiguity of real situations?
  • Can scenarios be answered by looking up documentation?
  • Do scenarios require weighing trade-offs?

Intervention: Add ambiguity. Remove artificial clarity. Include information that might be relevant but isn't, and omit information that would make the answer obvious. Test with real people—if everyone gets the same answer immediately, it's too simple.


CF5: Single Audience

Symptoms: Everyone gets the same training. Specialists are bored by basics. Generalists are overwhelmed by detail. One-size-fits-none.

Test:

  • Who are your actual audiences?
  • What depth does each audience need?
  • Does a general employee need the same competencies as a specialist?

Intervention: Define audience layers (typically General / Practitioner / Specialist). Map competencies to audiences. Layer content by depth:

  • L1: Rules without extensive justification (what to do)
  • L2: Principles behind rules (how to handle edge cases)
  • L3: Full technical detail (how to verify, audit, configure)

CF6: No Progression

Symptoms: Competencies exist but no clear order. Prerequisites unclear. No skip logic. Everyone follows the same path regardless of prior knowledge.

Test:

  • Which competencies require others as foundation?
  • What's the minimum viable path for each role?
  • Can someone with prior knowledge skip parts?

Intervention: Map dependencies. Build progression tree:

Foundation (everyone)
├── Prerequisite competencies
├─► Intermediate (builds on foundation)
└─► Role-specific branches (parallel tracks)

Define skip logic: what evidence allows skipping which modules?


CF7: No Verification Stakes

Symptoms: Assessment exists but doesn't gate anything. People skip or game it. No consequence for demonstrating vs. not demonstrating competency.

Test:

  • What decision does verification inform?
  • What happens if someone fails assessment?
  • Is there a real consequence for "not demonstrated"?

Intervention: Connect each verification to a decision:

  • Hiring: Does candidate advance?
  • Onboarding: Ready to work independently?
  • Access: Qualified for elevated permissions?
  • Promotion: Has developed required competency?

If verification doesn't connect to a decision, question whether it's worth doing.


CF8: No Feedback Loop

Symptoms: Framework built once and never updated. Questions keep arising that weren't anticipated. No visibility into what's not working.

Test:

  • How do you know what's not working?
  • What mechanism surfaces gaps in training, framework, or process?
  • When did this framework last change based on feedback?

Intervention: Implement feedback loop:

  1. Agent/support system logs questions with context
  2. Tag questions by competency/content area (or "unmapped")
  3. Regular review for patterns
  4. Route fixes to owners (training team, policy owners, tooling)
  5. Track when patterns lead to changes

CF9: Static Framework

Symptoms: Framework was built months/years ago. Reality has changed but framework hasn't. Questions reveal framework doesn't match current state.

Test:

  • When was this last reviewed?
  • What triggers an update?
  • Who owns maintenance?

Intervention: Define:

  • Review triggers (policy changes, incidents, new tools, feedback patterns)
  • Ownership (who updates what)
  • Version tracking (people trained on V1 vs. V2)
  • Cadence (minimum review frequency even without triggers)

CF10: Framework Operational

Symptoms: Competencies observable, scenarios tested, progression mapped, verification meaningful, feedback loop active, maintenance owned.

Indicators:

  • Can answer all previous state questions affirmatively
  • New hires reach competence faster
  • Repeat questions decrease
  • Framework has evolved based on feedback data
  • Skip logic personalizes paths based on demonstrated competency

Diagnostic Process

When someone presents a competency development need:

  1. Identify current state — What exists? Training content? Competency list? Scenarios? Assessment?
  2. Apply state diagnosis — Match symptoms to states above
  3. Ask clarifying questions — What decisions do people make? What failures have you seen?
  4. Explain the diagnosis — Name the state and what's missing
  5. Recommend next step — Point to specific template or intervention
  6. Validate progress — Check if intervention resolved the state

Key Questions by Phase

For Competency Identification

  • What decisions do people need to make with this knowledge?
  • What mistakes indicate someone lacks this competency?
  • What would you watch someone do to verify competency?
  • What's the failure mode this competency would prevent?

For Scenario Design

  • What realistic situation requires this judgment?
  • What information would be incomplete or ambiguous?
  • What would a weak response miss?
  • What distinguishes competent from exceptional?

For Audience Mapping

  • Who needs full depth? Who needs rules only?
  • Can the same content serve multiple audiences at different depths?
  • What's minimum viable competency for each role?

For Verification Design

  • What decision does this verification inform?
  • What evidence types are appropriate (scenario response, artifact, observed behavior)?
  • What distinguishes "partial" from "competent" from "strong"?

For Feedback Loops

  • What questions do people ask after training?
  • Which questions indicate training gaps vs. framework gaps vs. process gaps?
  • Who receives the signal? Who decides on fixes?

Anti-Patterns

PatternProblemFix
Document DumpConverting existing documentation into "training" without restructuringIdentify decisions documentation supports. Build backward from decisions to content.
Quiz FallacyAssessing competency with knowledge recall questionsReplace with scenarios requiring judgment. Can't answer by ctrl+F.
Universal TrainingOne training for all audiencesLayer content. Define minimum viable competency per role.
Orphan ScenarioScenario doesn't map to any defined competencyEither add the competency it tests, or cut the scenario.
Orphan ContentContent doesn't support any competencyEither identify the competency it serves, or cut the content.
Checkbox Completion"Completed training" without demonstrated competencyTie completion to demonstrated competency, not time spent.
Perfect on PaperFramework exists but isn't used; training continues as beforePilot with real people. Get feedback. Iterate.
Build-OnceFramework created, never updatedDefine triggers, owners, cadence for maintenance.

Templates

Competency Definition Template

## [Cluster Name] Competencies

| ID | Competency | Description |
|----|------------|-------------|
| [PREFIX]-1 | [Action verb phrase] | [Observable capability starting with "Can..."] |

Scenario Template

### Scenario: [Name]

**Core decision structure:** [What judgment is being tested]

**Interview variant:**
> [Generic situation]

**Assessment variant:**
> [Organization-specific situation]

**Competencies assessed:** [IDs]

**What good looks like:**
- [Consideration]

**Red flags:**
- [Weak response indicator]

Progression Template

Foundation (Role: Everyone)
├── [COMP-1]: [Name]
└── [COMP-2]: [Name]

├─► Intermediate (Role: [Role])
│   ├── [COMP-3]: [Name] (requires: COMP-1)
│   └── [COMP-4]: [Name] (requires: COMP-2)

└─► Specialist (Role: [Role])
    └── [COMP-5]: [Name] (requires: COMP-3, COMP-4)

Feedback Loop Template

## Feedback Loop Design

**Observation mechanism:**
- How questions are logged
- What context is captured
- How they're tagged to competencies

**Analysis cadence:** [frequency]

**Pattern categories:**
- Training gap: [who handles]
- Framework gap: [who handles]
- Process gap: [who handles]
- Tooling gap: [who handles]

**Change tracking:**
- How changes are documented
- How effectiveness is measured

Minimum Viable Framework

If starting small:

  1. 3-5 core competencies — the ones that matter most
  2. 2-3 scenarios — interview + assessment variants covering core competencies
  3. One layer of content — probably L2 (practitioner depth)
  4. Basic rubric — not demonstrated / partial / competent / strong
  5. One feedback signal — what questions do people ask after training?

Expand based on what you learn from using it.


Output Persistence

This skill writes primary output to files so work persists across sessions.

Output Discovery

Before doing any other work:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found or no entry for this skill, ask the user first:

- "Where should I save output from this competency-builder session?" - Suggest: explorations/competency/ or a sensible location for this project

  1. Store the user's preference:

- In context/output-config.md if context network exists - In .competency-builder-output.md at project root otherwise

Primary Output

For this skill, persist:

  • Diagnosed state - which competency framework state applies
  • Competency definitions - derived from failure modes
  • Scenario designs - test scenarios for each competency
  • Framework structure - progression model and dependencies
  • Feedback loop design - how gaps will be identified

Conversation vs. File

Goes to FileStays in Conversation
State diagnosisClarifying questions
Competency definitionsDiscussion of failure modes
Scenario templatesIteration on structure
Framework architectureReal-time feedback

File Naming

Pattern: {domain}-competency-{date}.md Example: ai-literacy-competency-2025-01-15.md

What This Skill Does NOT Do

  • Write training content — You help structure, they write content
  • Prescribe specific competencies — You help them discover theirs from failure modes
  • Assess whether existing training is "good" — You diagnose what's missing
  • Replace subject matter expertise — You provide methodology, they provide domain knowledge

Health Check Questions

During competency framework development, ask:

  1. Do all competencies describe observable capabilities (not knowledge states)?
  2. Does each scenario require judgment that can't be looked up?
  3. Is content layered appropriately for different audiences?
  4. Does verification connect to real decisions?
  5. Is there a mechanism to learn what's not working?
  6. Has the framework changed based on feedback?
  7. Can someone with prior knowledge skip parts?
  8. Does everyone follow the same path, or is it personalized?

Integration Points

SkillConnection
researchUse when building L3 content that requires domain expertise
framework-developmentRelated but distinct: frameworks capture knowledge; competency frameworks build capability
framework-to-mastraCompetency framework + feedback loop = deployable agent

Example Interaction

User: "We have a 40-page security policy. Everyone 'completes' the training but keeps making mistakes."

Diagnosis: CF1 (Content-First Trap)

Questions to ask:

  • What are the 3 most common mistakes people make after "completing" training?
  • What decisions do people make that require this knowledge?
  • When someone makes a mistake, what did they fail to recognize or do?

Guidance: "Each mistake suggests a competency gap. Let's work backward: if someone incorrectly handles sensitive data, the missing competency might be 'Can classify data according to organizational categories.' Once we have 3-5 competencies from failure modes, we'll design scenarios that test whether someone can actually apply the knowledge—not just recall it."


Source Framework

Derived from: references/competency-framework-development.md

平台分布

Claude Code

25.39%
按下载量换算498

OpenCode

23.79%
按下载量换算467

Antigravity

18.92%
按下载量换算371

Codex

12.02%
按下载量换算236

Gemini CLI

8.63%
按下载量换算169

windsurf

3.67%
按下载量换算72

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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