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competency-builder能力建设者

Agent Skill

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。

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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

3

许可证

MIT

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: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。

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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

简介

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。

SKILL.md

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

适合场景

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能力 5

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。

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