Repo Review Skill (Engineering Manager Edition)

This skill enables AI-powered repository analysis with three modes: contribution statistics, code quality assessment, and team/manager insights. Supports org-wide reviews, single repos, and saved repo groups.

Prerequisites

• Git CLI installed
• GitHub CLI (gh) for org-wide reviews
• Optional: Python 3.10+ with matplotlib for PNG chart generation

Quick Start

Review https://github.com/org/repo
Review the UP organization
Review my side-projects group

Progressive Onboarding

On first use, gather context through conversation:

Initial Questions

1. Role: Engineering Manager | Tech Lead | IC
2. Focus: Full review | Quick stats | Code quality only
3. Time period: 30 days | 90 days | YTD | Custom

Save preferences to config.yaml for future sessions.

Follow-up Questions (as needed)

• "I found 5 contributors. Focus on anyone specific?"
• "Compare against previous review?"
• "Flag contributors with < X commits?"

---

Analysis Modes

Mode 1: Contribution Statistics

Gather quantitative metrics using git commands:

# Clone repo to temp directory
git clone --quiet <repo_url> /tmp/repo_review_temp

# Contribution stats by author
git log --numstat --format="COMMIT|%H|%an|%ad" --date=short --since="2025-01-01" --all

# Weekly breakdown
git log --format="%ad" --date=short --since="2025-01-01" | sort | uniq -c

# Files touched by author
git log --author="Name" --name-only --pretty=format: | sort | uniq -c | sort -rn

# File type breakdown
git log --numstat --format="" | awk '{print $3}' | grep -oE '\.[^.]+$' | sort | uniq -c | sort -rn

Output metrics:

• Commits per author
• Lines added/deleted/net per author
• File type breakdown (frontend/backend/config/infra/docs)
• Weekly/monthly activity patterns

Mode 2: Code Quality Review

Examine the codebase for:

Architecture & Patterns

• Project structure organization
• Component/module boundaries
• DRY compliance
• Separation of concerns

Type Safety

• TypeScript strictness
• any usage
• Proper type exports

Error Handling

• Try/catch patterns
• Error boundaries
• Validation at boundaries

Database/API Patterns

• Query structure
• N+1 detection
• Input validation

Security

• Auth implementation
• Secret handling
• Input sanitization

Testing Indicators

• Test file presence
• Coverage indicators
• Test patterns

Mode 3: Team/Manager Assessment

Combine quantitative data with qualitative code review:

Per-Contributor Analysis:

• Volume and consistency
• Scope of work (full-stack vs narrow)
• Quality signals
• Growth indicators

Team Health:

• Bus factor
• Knowledge silos
• Cross-functional work
• Velocity trends

---

Review Targets

1. Single Repository

Review https://github.com/org/repo
Review https://github.com/org/repo --since 2025-06-01

2. Organization-Wide

Review the UP organization
Review all repos in UP org

Uses GitHub CLI:

gh repo list UP --limit 100 --json name,sshUrl,url

3. Saved Groups

Review my side-projects group
Review client-work group

4. Managing Groups

Add https://github.com/user/repo to side-projects
Create a new group called "experiments"
Remove old-project from experiments
Show all my saved groups

---

Visualization Options

Mermaid Diagrams (for markdown reports)

Contribution Timeline:

gantt
    title Contribution Timeline
    dateFormat YYYY-MM-DD
    section Contributor1
    Feature A     :2025-12-30, 2d
    Feature B     :2026-01-02, 1d
    section Contributor2
    Bug Fix       :2026-01-01, 1d

Work Breakdown:

pie title Work Breakdown
    "Frontend" : 45
    "Backend" : 30
    "Config" : 15
    "Docs" : 10

ASCII Charts (for terminal/quick view)

Author          | Net LoC | Contribution
----------------|---------|----------------------------------
Alice           |   2,872 | ████████████████████████████ 100%
Bob             |   1,020 | ████████████░░░░░░░░░░░░░░░░  35%
Charlie         |      18 | █░░░░░░░░░░░░░░░░░░░░░░░░░░░   1%

Weekly Trend:

Week 1: ████████████ 1,200 LoC
Week 2: ███████████████ 1,450 LoC ↑
Week 3: █████████ 890 LoC ↓ ⚠️

Script Charts (for presentations)

Run scripts/repo_review_om.py for matplotlib PNG generation:

python scripts/repo_review_om.py --repo https://github.com/org/repo --chart

---

Manager-Focused Outputs

Performance Review Language

Strong Performer:

"[Name] demonstrated strong capabilities, delivering [X] features across [Y] commits totaling [Z] net lines. Notable contributions include [specific feature]. Their work showed [quality indicator - e.g., proper error handling, TypeScript usage, test coverage]."

Solid Contributor:

"[Name] contributed consistently with [X] commits and [Y] net lines. Primary focus was [area]. Recommend expanding into [adjacent area] for growth."

Needs Attention:

"[Name] had limited participation with [X] commits totaling [Y] lines. Contributions were confined to [narrow scope]. Recommend 1:1 to understand blockers and assign stretch goals."

1:1 Conversation Starters

Pattern Detected	Suggested Questions
Low participation	"I noticed fewer commits recently. What's blocking you? How can I help clear obstacles?"
Narrow scope (UI only)	"You've done great frontend work. Interested in backend exposure? I can pair you with [name]."
High volume, quality concerns	"You're shipping fast which is great. Let's talk about our code review process and testing practices."
Declining trend	"Your output has shifted. Are you feeling challenged enough? Burned out? Something outside work?"
Strong performance	"Your auth implementation was solid. Ready to take on a larger feature? Lead a project?"
Git config issues	"Quick housekeeping - let's fix your git config so your commits are consistent."

Growth/Promotion Readiness

Junior → Mid-Level Signals:

• Works across frontend AND backend
• Writes database migrations/schema changes
• Fixes bugs introduced by others (not just own code)
• Adds tests without being prompted
• Clear commit messages with context
• Participates in code review

Mid → Senior Signals:

• Designs features end-to-end
• Mentors juniors (visible in PR reviews)
• Identifies and addresses technical debt
• Documents architectural decisions
• Considers security implications
• Optimizes for maintainability

Red Flag Detection

Red Flag	Indicators	Recommended Action
Disengagement	< 1 commit/week sustained, shrinking scope	Urgent 1:1, understand root cause
Burnout risk	High volume followed by sudden drop	Discuss workload, consider time off
Git identity issues	Multiple author names for same person	Fix git config, merge stats in analysis
Narrow specialization	Only touches one file type	Assign cross-functional tasks
Knowledge silo	Only person who touches critical code	Pair programming, documentation push
Declining quality	Increasing bug fixes on own code	Code review focus, testing discussion

Team Health Metrics

Velocity Trend:

Period      | Team LoC | Trend    | Notes
------------|----------|----------|------------------
Week 1      |    1,200 | baseline |
Week 2      |    1,450 | ↑ 21%    | Sprint push
Week 3      |      890 | ↓ 39%    | ⚠️ Investigate
Week 4      |    1,100 | ↑ 24%    | Recovery

Knowledge Distribution:

• Bus Factor: How many people can modify each critical area?
• Silo Score: % of code touched by only one person
• Cross-functional Index: % of contributors working across stack

Contribution Balance:

Ideal: Relatively balanced contributions
⚠️ Warning: Top contributor has >70% of commits
🚨 Critical: One person has >90% of commits

---

Configuration

The skill uses config.yaml for persistent settings. Created on first use.

Config Structure

# Default analysis settings
defaults:
  since: "2025-01-01"
  analysis_modes:
    - contributions
    - quality
    - team
  output_format: markdown  # markdown | ascii | json
  role: engineering_manager  # engineering_manager | tech_lead | ic

# Saved organizations
orgs:
  up:
    github_org: "UP"
    description: "UP Company repositories"
    active: true
    contributors:
      - name: "Alice Smith"
        aliases: ["alice", "asmith"]
        role: "Senior Engineer"
        active: true
      - name: "Bob Jones"
        aliases: ["bob", "bjones"]
        role: "Junior Engineer"
        active: true
      - name: "Former Employee"
        aliases: ["former"]
        role: "Engineer"
        active: false  # No longer with team
    exclude_authors:
      - "dependabot[bot]"
      - "github-actions[bot]"
      - "renovate[bot]"

# Saved repo groups (for non-org collections)
groups:
  side-projects:
    description: "Personal weekend experiments"
    active: true
    repos:
      - "https://github.com/user/project-a"
      - "https://github.com/user/project-b"
      
  client-work:
    description: "Freelance client projects"
    active: true
    repos:
      - "https://github.com/client/app"

  archived:
    description: "Old projects for reference"
    active: false
    repos:
      - "https://github.com/user/old-thing"

# Session tracking
last_session:
  target: "up"
  target_type: "org"  # org | group | repo
  date: "2026-01-10"

Managing Config

Add contributor:

Add contributor "New Person" with alias "newperson" to UP org

Deactivate contributor:

Mark "Former Employee" as inactive in UP org

Update org:

Set UP org as inactive

---

Example Workflows

Weekly Team Standup Prep

User: "Quick stats on UP org for the past week"

AI: [Fetches last 7 days, shows commit counts per active contributor, flags anyone with 0 commits]

Monthly Review

User: "Full review of UP org for December"

AI: [Comprehensive analysis with charts, per-contributor breakdown, team health metrics, comparison to November if available]

1:1 Preparation

User: "Prep 1:1 notes for Bob based on UP contributions"

AI: [Pulls Bob's stats across all org repos, correlates with code quality observations, generates talking points and growth recommendations]

New Hire Onboarding Check

User: "How is the new junior doing in UP org? Started 2 weeks ago."

AI: [Filters to last 2 weeks, compares to typical onboarding velocity, identifies areas of focus, suggests pairing opportunities]

Quarterly Summary

User: "Generate Q4 summary for UP team"

AI: [Aggregates Oct-Dec data, identifies top contributors, flags concerns, generates executive summary suitable for leadership]

Project Kickoff

User: "Add https://github.com/client/new-project to client-work and give me initial review"

AI: [Adds to group, clones repo, establishes baseline metrics, identifies current contributors and code state]

---

Troubleshooting

GitHub CLI Not Authenticated

Error: gh: not logged in

Fix: Run `gh auth login` and follow prompts

Private Repo Access

Error: Repository not found (404)

Fix: Ensure gh CLI has access, or use SSH URL if you have keys configured

Large Org Timeout

For orgs with 50+ repos, consider:
1. Running with --limit flag
2. Excluding archived repos
3. Focusing on specific repos via group

Git Config Issues (Multiple Authors)

Contributor showing as multiple people:

Fix: Have them run:
  git config --global user.name "Consistent Name"
  git config --global user.email "consistent@email.com"

Workaround: Add all variations to aliases in config.yaml

---

Script Reference

For advanced chart generation, use the included Python script:

cd skills/repo-review/scripts

# Single repo with chart
python repo_review_om.py --repo https://github.com/org/repo --chart

# Org-wide
python repo_review_om.py --all --dir /tmp/org-repos

# Date range
python repo_review_om.py --repo URL --since 2025-06-01 --until 2025-12-31

# Exclude docs
python repo_review_om.py --repo URL --no-docs

Output: CSV data file + PNG chart (if --chart flag used)