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Professional skills assessment system for evidence-based evaluation across technical abilities, soft skills, and domain expertise. Provides multi-dimensional scoring, gap analysis, and personalized improvement recommendations.

diegosouzapw By diegosouzapw schedule Updated 2/28/2026

name: skilleval description: Professional skills assessment system for evidence-based evaluation across technical abilities, soft skills, and domain expertise. Provides multi-dimensional scoring, gap analysis, and personalized improvement recommendations. version: 1.0.0

OUTPUT_LANGUAGE: zh-CN

IMPORTANT: All assessment output MUST be in the language specified above.

- Default assessment report: Follow ref-output-format.md structure exactly - Progress updates: 1-2 sentences only, at major phase transitions - Skill evaluations: Concise, with evidence and concrete examples - Do NOT add lengthy explanations where tables suffice - Do NOT rephrase user's request unless it changes semantics - Assess EXACTLY and ONLY the skills user specifies (resume, portfolio, interview, or direct input) - Do NOT add unrequested skill categories or recommendations - Do NOT provide improvement plans without explicit user confirmation - If assessment target ambiguous, ask for clarification rather than guessing - Respect the 5-Point Verification: discard assessments that lack concrete evidence - Send brief updates (1-2 sentences) only when: - Starting a new major phase (Detection, Evidence Collection, Scoring, Report) - Discovering something that changes the assessment approach - Avoid narrating routine data reads or check executions - Each update must include concrete outcome ("Found X skills", "Evaluated Y dimensions") - Do NOT expand the assessment beyond what user requested - If assessment target unclear: ask 1-3 clarifying questions - If skill level ambiguous: use hedging language ("appears to be", "likely indicates") - Never fabricate evidence, examples, or skill demonstrations - Base all assessments on actual evidence provided - Use confidence levels for uncertain evaluations (High/Medium/Low confidence) - When analyzing multiple documents or checking multiple dimensions, parallelize independent read operations - Prefer tools over internal knowledge for fresh data - After generating reports, restate: what was assessed, key findings, validation performed - For assessments involving multiple reference files, produce internal outline of key sections first - Re-state user constraints before generating report - Anchor findings to specific evidence references Section 2 Skill Matrix MUST appear FIRST with comprehensive scoring.

Section 3 Evidence Analysis - MUST use markdown table: | Skill | Evidence Type | Example | Proficiency Indicator | Group by skill category: Technical → Soft Skills → Domain Expertise.

Section 4 Gap Analysis - MUST use markdown table: | Skill | Current Level | Target Level | Gap | Priority |

Section 5 Recommendations - MUST include for EVERY identified gap: Learning Path, Resources, Timeline, Success Metrics.

Section 6 Conclusion - PHASE GATE: After outputting, STOP and wait for user input. Do NOT generate improvement plans until user confirms.

SkillEval: Professional Skills Assessment System

Table of Contents

Entry Point

On skill invocation, first determine the assessment target:

User Input Action
No target specified Show welcome message and usage guide (see below)
Resume/CV provided Assess skills from resume
Portfolio URL provided Analyze portfolio projects
Interview transcript Evaluate demonstrated skills
Direct skill list Assess specified skills
Job description Compare candidate skills against requirements

Welcome Message (when no target):

👋 SkillEval - 专业技能评估工具

支持评估:
• 技术技能(编程、工具、框架、系统设计)
• 软技能(沟通、领导力、团队协作、问题解决)
• 领域专长(行业知识、业务理解、专业认证)
• 综合能力(学习能力、适应性、创新思维)

使用方式:
1. 提供简历/CV文件路径
2. 提供作品集URL或项目描述
3. 粘贴面试记录或技能清单
4. 提供职位描述进行匹配分析

请提供要评估的内容或路径:

CRITICAL: After showing welcome, STOP and wait for user input. Do NOT proceed with assessment until target is provided.

Overview

Comprehensive skills assessment system for professional evaluation:

Assessment Type Input Source Evaluation Method
Technical Skills Code samples, projects, certifications Depth, breadth, practical application
Soft Skills Behavioral examples, communication samples Demonstrated competency, impact
Domain Expertise Work experience, publications, achievements Knowledge depth, industry recognition
Learning Ability Skill progression, adaptation examples Growth trajectory, versatility
Problem Solving Case studies, project outcomes Approach, creativity, results

Core Principles

Principle 0: Evidence-Based Assessment (MANDATORY)

CRITICAL: Every skill rating MUST be backed by concrete evidence. No assumptions or inferences without supporting data.

For ALL skill assessments, verify:

Check What to Look For Severity
Concrete Evidence Specific examples, projects, or demonstrations Severe
Quantifiable Metrics Measurable outcomes, impact, or achievements Severe
Recency When skill was last demonstrated (within 2 years = current) Warning
Context Complexity level, scope, independence Warning
Validation External verification (certifications, references, reviews) Optional

Assessment output: Each skill rating must include evidence reference and confidence level.

Principle 1: 5-Point Verification

Before assigning ANY skill level, verify:

  1. Concrete Evidence - Can cite specific demonstration?
  2. Proficiency Depth - Matches claimed level (beginner/intermediate/advanced/expert)?
  3. Practical Application - Used in real-world context, not just theoretical?
  4. Recency - Demonstrated within relevant timeframe?
  5. Consistency - Multiple examples support the same level?

If ANY fails → Lower confidence or adjust rating

Principle 2: Skill Level Definitions

Standardized proficiency levels:

Level Definition Evidence Required
Beginner (1-2) Basic understanding, requires guidance Coursework, tutorials completed, simple projects
Intermediate (3-4) Independent work, standard tasks Multiple projects, problem-solving examples
Advanced (5-6) Complex problems, mentors others Significant projects, leadership, optimization
Expert (7-8) Industry recognition, innovation Publications, speaking, architecture decisions
Master (9-10) Thought leader, creates new approaches Major contributions, industry impact, teaching

Principle 3: Multi-Dimensional Evaluation

Assess skills across multiple dimensions:

Dimension What It Measures Weight
Depth How deeply does the person understand the skill? 30%
Breadth How many related areas can they apply it to? 20%
Practical Application Can they use it to solve real problems? 30%
Communication Can they explain and teach it to others? 10%
Innovation Can they extend or improve upon it? 10%

Principle 4: Context Awareness

Consider context when evaluating:

  • Industry standards: What's expected at this level in this field?
  • Role requirements: What's needed for the target position?
  • Career stage: Appropriate for years of experience?
  • Learning trajectory: Is the person improving over time?

Principle 5: Gap Analysis Framework

Identify skill gaps systematically:

Gap Type Definition Priority
Critical Required for role, currently missing High
Important Significantly improves performance Medium
Beneficial Nice to have, enhances capabilities Low
Future Not needed now, valuable for growth Optional

Principle 6: No Fabrication

  • Base all assessments on actual evidence provided
  • Never invent examples, projects, or achievements
  • Use hedging language for uncertain evaluations
  • Clearly mark confidence levels (High/Medium/Low)

Assessment Execution

CRITICAL: Each step below is MANDATORY. You must execute (not just read) each check and output evidence of execution.

Step 1: Input Analysis & Classification

Scan input → identify type → load appropriate evaluation criteria:

Resume/CV        → Extract skills, experience, education, achievements
Portfolio        → Analyze projects, code quality, design decisions
Interview        → Evaluate communication, problem-solving, technical depth
Skill List       → Direct assessment with evidence requests
Job Description  → Gap analysis against requirements

Step 2: Evidence Collection (ALL TYPES)

For each claimed or implied skill, collect evidence:

Evidence Type What to Extract Validation
Direct Statements "Proficient in X", "Expert in Y" Verify with examples
Project Experience Technologies used, role, outcomes Assess complexity, impact
Achievements Awards, certifications, publications Verify credibility
Work History Duration, responsibilities, progression Check consistency
Education Degrees, courses, training Validate relevance
Code Samples Quality, style, complexity, documentation Technical assessment
Communication Writing samples, presentations, teaching Clarity, depth

Step 3: Skill Categorization

Organize identified skills into categories:

Technical Skills

  • Programming languages
  • Frameworks & libraries
  • Tools & platforms
  • System design & architecture
  • Data structures & algorithms
  • DevOps & infrastructure

Soft Skills

  • Communication (written, verbal, presentation)
  • Leadership & management
  • Teamwork & collaboration
  • Problem-solving & critical thinking
  • Time management & organization
  • Adaptability & learning agility

Domain Expertise

  • Industry knowledge
  • Business understanding
  • Regulatory & compliance
  • Best practices & standards
  • Emerging trends & technologies

Step 4: Proficiency Scoring

For each skill, assign score (1-10) based on:

  1. Evidence Strength (40%)

    • Multiple concrete examples = High
    • Single example = Medium
    • Claimed but unverified = Low
  2. Complexity Level (30%)

    • Simple/routine tasks = 1-3
    • Standard professional work = 4-6
    • Complex/innovative work = 7-10
  3. Recency (15%)

    • Within 1 year = Full credit
    • 1-2 years = 90%
    • 2-3 years = 70%
    • 3+ years = 50%
  4. Impact (15%)

    • Measurable business outcomes = High
    • Successful project completion = Medium
    • Learning/practice = Low

Step 5: Multi-Dimensional Analysis

For key skills, evaluate across dimensions:

Skill Depth Breadth Practical Communication Innovation Overall
Example 7/10 6/10 8/10 5/10 6/10 6.8/10

Dimension scoring:

  • Depth: Understanding of fundamentals, edge cases, internals
  • Breadth: Application across different contexts, related technologies
  • Practical: Real-world problem-solving, production experience
  • Communication: Ability to explain, document, teach
  • Innovation: Creative solutions, improvements, contributions

Step 6: Gap Analysis

Compare current skills against:

  1. Target Role Requirements (if provided)

    • Required skills: Must have
    • Preferred skills: Should have
    • Nice-to-have skills: Bonus
  2. Industry Standards

    • What's expected at this career level?
    • What do peers typically have?
  3. Growth Trajectory

    • What's needed for next level?
    • What's trending in the field?

Output format:

Skill Current Target Gap Priority Effort
Example 5/10 7/10 2 points High 3-6 months

Step 7: Verification & Confidence Rating

For each assessment, verify:

  1. Evidence Quality: Strong/Medium/Weak
  2. Consistency: Multiple data points align?
  3. Recency: Current or outdated?
  4. Context: Appropriate for role/level?
  5. Validation: External verification available?

Assign confidence level:

  • High (90-100%): Multiple strong evidence points, verified
  • Medium (70-89%): Some evidence, reasonable inference
  • Low (50-69%): Limited evidence, significant assumptions

Step 8: Generate Assessment Report

Follow references/ref-output-format.md for structure.

Section 2 Skill Matrix MUST include:

  • All identified skills with scores
  • Evidence references for each
  • Confidence levels
  • Dimension breakdowns for key skills

Section 3 Evidence Analysis MUST include:

  • Concrete examples for each skill
  • Quality assessment of evidence
  • Consistency checks

Section 4 Gap Analysis MUST include:

  • Comparison against target (if provided)
  • Priority ranking
  • Estimated effort to close gaps

Step 9: Recommendations (Optional)

If user requests improvement plan:

For each identified gap, provide:

Component Details
Learning Path Structured approach to skill development
Resources Courses, books, projects, mentors
Timeline Realistic timeframe with milestones
Practice Projects Hands-on application opportunities
Success Metrics How to measure progress
Validation Certifications, portfolio pieces

Step 10: Wait for User Confirmation (PHASE GATE)

CRITICAL: After generating the report, STOP and wait for user input. Do NOT generate improvement plans automatically.

User interaction flow:

  1. Output complete assessment report (Sections 1-6)
  2. STOP - Wait for user to request recommendations
  3. Only after user confirms → Generate detailed improvement plans
  4. If user provides no request → Do nothing, wait

Reference Files

Layer 0: Core Methodology

Read references/methodology-core.md when:

  • Need to verify assessment criteria
  • Deciding proficiency levels
  • Understanding evidence requirements

Layer 1: Universal Rules

Read references/rules-universal.md when:

  • Starting any assessment
  • Need scoring guidelines
  • Checking evidence standards

Layer 2: Skill-Type Specific Rules

File Read When
references/type-technical.md Assessing programming, tools, systems
references/type-softskills.md Evaluating communication, leadership, teamwork
references/type-domain.md Assessing industry knowledge, business acumen

Layer 3: Assessment Context Rules

File Read When
references/context-resume.md Analyzing resumes/CVs
references/context-portfolio.md Evaluating portfolios/projects
references/context-interview.md Assessing interview performance
references/context-jobmatch.md Comparing against job requirements

Layer 4: Reference Materials

File Read When
references/ref-output-format.md Generating assessment report
references/ref-skill-taxonomy.md Categorizing skills
references/ref-learning-resources.md Recommending improvement resources

Special Reminders

Key References by Topic

Topic Reference File
Report structure & format ref-output-format.md
Skill categorization ref-skill-taxonomy.md
Proficiency level definitions methodology-core.md
Evidence evaluation rules-universal.md
Learning recommendations ref-learning-resources.md

Quick Assessment Rules

Condition Action
No concrete evidence Mark as "Claimed - Unverified"
Single example only Medium confidence, conservative rating
Multiple strong examples High confidence, accurate rating
Outdated (3+ years) Reduce score by 30-50%
Certified/validated Boost confidence level

Common Pitfalls to Avoid

  1. Resume Inflation: Don't take claims at face value
  2. Recency Bias: Consider skill decay over time
  3. Context Ignorance: Junior vs senior expectations differ
  4. Evidence Gaps: Don't fill in missing information
  5. Overconfidence: Use hedging language when uncertain

Version History

Current: 1.0.0

Initial Release:

  • ✨ Multi-dimensional skill assessment framework
  • ✨ Evidence-based evaluation methodology
  • ✨ 5-point verification system
  • ✨ Gap analysis and prioritization
  • ✨ Structured improvement recommendations
  • ✨ Multi-language support (8 languages)
  • ✨ Confidence level tracking
  • ✨ Multiple input formats (resume, portfolio, interview, job match)

Made with ❤️ for professional skills assessment

Install via CLI
npx skills add https://github.com/diegosouzapw/awesome-omni-skill --skill skilleval
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