Agent skill · Data & Analytics

curriculum-analyze-outcomes

Calculate objective mastery rates, analyze performance distributions, identify achievement gaps, and generate learning analytics dashboards. Use when analyzing assessment data, measuring outcomes, or generating reports. Activates on "analyze results", "learning analytics", "performance data", or "outcome measurement".

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill curriculum-analyze-outcomes --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 8 KB
Bundled scripts: none
Path: skills/analysis/curriculum-analyze-outcomes/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Learning Analytics & Outcome Measurement Analyze assessment data to measure learning objective mastery, identify trends, visualize performance, and generate actionable insights. ## When to Use - Analyze assessment results - Calculate mastery rates - Identify performance patterns - Generate analytics reports - Measure learning outcomes ## Required Inputs - **Assessment Data**: Student scores, responses - **Learning Objectives**: What was assessed - **Demographics** (optional): For gap analysis - **Historical Data** (optional): For trends ## Workflow ### 1. Load and Validate Data Import: - Assessment scores by student - Item-level responses - Learning objective mappings - Student demographic data (if analyzing equity) - Timestamps for trend analysis ### 2. Calculate Objective Mastery Rates For each learning objective: ```markdown ## Objective LO-1.1 Mastery Analysis **Objective**: Students will identify the role of chlorophyll in photosynthesis **Items Assessing This Objective**: MC-1, MC-5, SA-2 **Mastery Threshold**: 75% correct **Results**: - **Mastered** (≥75%): 23 students (76.7%) - **Approaching** (50-74%): 5 students (16.7%) - **Needs Support** (<50%): 2 students (6.7%) **Av

What's inside
Steps it walks through
  1. When to Use
  2. Required Inputs
  3. Workflow
  4. 1. Load and Validate Data
  5. 2. Calculate Objective Mastery Rates
  6. 3. Identify High/Low Performing Objectives
  7. 4. Analyze Achievement Gaps
  8. 5. Item Analysis (Psychometrics)
  9. 6. Generate Analytics Dashboard
  10. 7. CLI Interface
  11. Composition with Other Skills
  12. Exit Codes
Ships with 1 file
  • metadata.json
Commands it runs
Analyze single assessment
Course-level analysis
Trend analysis
Equity focus
Help
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About this skill
What does the curriculum-analyze-outcomes skill do?

Calculate objective mastery rates, analyze performance distributions, identify achievement gaps, and generate learning analytics dashboards. Use when analyzing assessment data, measuring outcomes, or generating reports. Activates on "analyze results", "learning analytics", "performance data", or "outcome measurement".

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill curriculum-analyze-outcomes --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going