AI Skill Report Card

Reviewing Feedback

B+78·Feb 12, 2026·Source: Web

Quick Start

Current feedback: [paste feedback/scorecard here]
Context: [what was being evaluated]

Analysis:
- Strengths: [key positive points]
- Gaps: [specific areas needing improvement]
- Priority actions: [top 3 actionable items]

Workflow

  1. Parse the feedback structure

    • Identify scoring criteria/rubrics
    • Note quantitative scores vs qualitative comments
    • Separate overall themes from specific details
  2. Extract key insights

    • Strengths to leverage
    • Weaknesses requiring attention
    • Patterns across multiple feedback points
  3. Prioritize improvements

    • Impact vs effort analysis
    • Quick wins vs long-term development
    • Dependencies between improvement areas
  4. Create action plan

    • Specific, measurable next steps
    • Timeline for implementation
    • Success metrics

Progress:

  • Feedback parsed and categorized
  • Key strengths and gaps identified
  • Improvement priorities ranked
  • Action plan created with timelines

Examples

Example 1: Input: "Code review feedback: Good logic flow (8/10), but variable naming unclear (4/10) and missing error handling (3/10)" Output:

  • Strengths: Strong algorithmic thinking
  • Priority fixes: 1) Add try-catch blocks, 2) Rename variables to be descriptive
  • Quick win: Variable renaming (30 min), Error handling (2 hours)

Example 2: Input: "Presentation scored 7/10 - clear content but monotone delivery and weak conclusion" Output:

  • Strengths: Well-organized information
  • Improvements: Voice modulation practice, stronger closing statements
  • Action: Record practice sessions, prepare 3 conclusion templates

Best Practices

  • Look for feedback patterns, not just individual comments
  • Separate ego from analysis - treat feedback as data
  • Quantify vague feedback when possible ("improve communication" → "speak 20% slower")
  • Balance addressing weaknesses with leveraging strengths
  • Set specific deadlines for implementing changes

Common Pitfalls

  • Don't dismiss positive feedback as unimportant
  • Don't try to fix everything at once - prioritize
  • Don't assume you understand feedback without clarifying ambiguous points
  • Don't focus only on negative feedback while ignoring what's working well
  • Don't create improvement plans without concrete, measurable actions
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Grade B+AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
14/15
Workflow
14/15
Examples
18/20
Completeness
16/20
Format
15/15
Conciseness
13/15