Complete Contribution Strategy - Context Aware

I'll analyze everything needed for your successful contribution based on your current context and work.

Strategic Thinking Process

<think> For a successful contribution, I need to analyze:

1. Current Work Context

   • What has been done in this session?
   • Are we mid-implementation or post-completion?
   • What type of changes were made (feature, fix, refactor)?
   • Is the work ready for contribution?

2. Project Type & Standards

   • Is this open source, company, or personal project?
   • What are the contribution guidelines?
   • Are there specific workflows to follow?
   • What quality gates exist (tests, lint, reviews)?

3. Contribution Strategy

   • Should this be one PR or multiple?
   • Which issues does this work address?
   • What documentation needs updating?
   • Who should review this?

4. Pre-flight Checklist

   • Do all tests pass?
   • Is the code properly formatted?
   • Are there any lint warnings?
   • Is documentation updated?
   • Are commits well-organized? </think>

Token Optimization Strategy

Target: 65% reduction (3,000-5,000 → 1,000-1,800 tokens)

This skill uses aggressive optimization to minimize token usage while providing comprehensive contribution readiness assessment.

Core Optimization Principles

1. Early Exit Pattern (Saves 70-90% tokens)

# Check if already documented
if [ -f "CONTRIBUTING.md" ] && grep -q "contribution" CONTRIBUTING.md; then
  echo "✓ Contribution guidelines exist - use for reference"
  exit 0
fi

# Mandatory pre-flight checks FIRST
npm test || exit 1  # Stop if tests fail (saves full analysis)
npm run lint || exit 1
npm run build || exit 1

2. Git Analysis for Contribution Patterns (Zero file reads)

# Analyze contribution history without reading files
git log --format="%H|%s|%an" -n 50 > /tmp/contribution_patterns.txt
git log --all --since="6 months ago" --format="%ae" | sort | uniq -c | sort -rn | head -5
git log --all --grep="Fixes #" --grep="Closes #" -E --format="%H %s"

# PR patterns from branches
git branch -r | grep -E "(feature|fix|hotfix|bugfix)" | wc -l
git config --get remote.origin.url  # Detect GitHub/GitLab/etc

3. Template-Based Readiness Assessment (1 Read vs Many)

# Read only the essentials
[ -f "CONTRIBUTING.md" ] && Read CONTRIBUTING.md
[ -f ".github/PULL_REQUEST_TEMPLATE.md" ] && Read .github/PULL_REQUEST_TEMPLATE.md

# Use templates to drive checklist (not deep analysis)
checklist="
- [ ] Tests passing (bash check)
- [ ] Lint passing (bash check)
- [ ] Build passing (bash check)
- [ ] Commits follow convention (git log check)
- [ ] Branch follows naming (git branch check)
- [ ] PR template exists (file check)
"

4. Bash-Based Validation Checks (External tools, minimal tokens)

# All checks use Bash, not file reads
npm test 2>&1 | tail -5          # Test status
npm run lint 2>&1 | tail -5      # Lint status
npm run build 2>&1 | tail -5     # Build status

# Git hook validation
[ -f ".git/hooks/pre-commit" ] && echo "✓ Pre-commit hooks"
[ -f ".git/hooks/commit-msg" ] && echo "✓ Commit-msg hooks"

# CI configuration check
[ -f ".github/workflows/ci.yml" ] && echo "✓ GitHub Actions CI"
[ -f ".gitlab-ci.yml" ] && echo "✓ GitLab CI"
[ -f "Jenkinsfile" ] && echo "✓ Jenkins"

5. Project Structure Caching (Reuse /understand results)

# Check for existing analysis
if [ -f ".claude/cache/understand/project_structure.json" ]; then
  # Reuse structure instead of re-analyzing
  PROJECT_TYPE=$(jq -r '.project_type' .claude/cache/understand/project_structure.json)
  TEST_FRAMEWORK=$(jq -r '.test_framework' .claude/cache/understand/project_structure.json)
  BUILD_TOOL=$(jq -r '.build_tool' .claude/cache/understand/project_structure.json)
else
  # Quick detection (no deep analysis)
  [ -f "package.json" ] && PROJECT_TYPE="node"
  [ -f "pom.xml" ] && PROJECT_TYPE="java"
  [ -f "Cargo.toml" ] && PROJECT_TYPE="rust"
fi

6. Checklist-Based Validation (Not Deep Analysis)

Instead of:
❌ Read all test files → Analyze coverage → Generate report (2,000 tokens)

Do:
✅ Run `npm test -- --coverage` → Parse output (200 tokens)

Instead of:
❌ Read all source files → Check style → Report violations (3,000 tokens)

Do:
✅ Run `npm run lint` → Parse exit code (100 tokens)

Token Usage Breakdown

Unoptimized (3,000-5,000 tokens):

• Read CONTRIBUTING.md, README.md, CHANGELOG.md (800 tokens)
• Read .github templates and workflows (600 tokens)
• Analyze all changed files for style compliance (1,000 tokens)
• Read test files to verify coverage (500 tokens)
• Analyze commit history patterns (400 tokens)
• Generate detailed contribution guide (700 tokens)

Optimized (1,000-1,800 tokens):

• Git analysis for patterns (Bash commands, 150 tokens)
• Read CONTRIBUTING.md only if exists (200 tokens)
• Read PR template only if exists (150 tokens)
• Bash checks for tests/lint/build (200 tokens)
• Checklist-based validation (300 tokens)
• Template-based readiness report (400 tokens)

Savings: 65% reduction

Optimization Techniques Applied

A. Git-First Analysis (Saves 40% tokens)

# Instead of reading files, use git
git diff --stat origin/main...HEAD  # Changed files
git log --oneline -n 10              # Recent commits
git log --format="%s" | grep -E "^(feat|fix|docs|test)"  # Convention check
git branch --show-current            # Current branch
git remote get-url origin            # Repository URL

B. Cache Contribution Metadata

// .claude/cache/contributing/metadata.json
{
  "project_type": "open_source",
  "workflow": "github_flow",
  "pr_template": ".github/PULL_REQUEST_TEMPLATE.md",
  "required_checks": ["test", "lint", "build"],
  "commit_convention": "conventional_commits",
  "branch_pattern": "feature/*",
  "cached_at": "2026-01-27T10:00:00Z"
}

C. Progressive Disclosure (Saves 50% on simple cases)

Quick Path (500 tokens):
- Pre-flight checks only
- All passing → Ready to contribute
- Any failing → Show fix commands

Standard Path (1,000 tokens):
- Pre-flight checks
- Read CONTRIBUTING.md
- Generate checklist
- Show next steps

Full Path (1,800 tokens):
- All above
- Analyze git patterns
- Compare with project standards
- Generate detailed action plan

D. Focus Area Flags (User-controlled scope)

# Minimal check
contributing --pre-flight        # 500 tokens - just validation

# Targeted checks
contributing --docs              # 600 tokens - docs only
contributing --pr-prep           # 800 tokens - PR preparation only
contributing --test-status       # 400 tokens - test validation only

# Full analysis (when needed)
contributing                     # 1,800 tokens - complete assessment

E. Reuse Shared Caches

Caches shared with other skills:
- /understand → Project structure, tech stack
- /test → Test framework, coverage config
- /commit → Commit conventions
- /review → Code patterns, standards

Instead of re-analyzing:
1. Check for existing cache
2. Validate cache is recent (< 24 hours)
3. Reuse cached data
4. Only re-analyze if cache miss

Implementation Guidelines

Pattern 1: Early Exit on Simple Cases

# Check if work is ready (90% of cases)
if npm test && npm run lint && npm run build; then
  echo "✓ All checks pass - Ready to contribute"
  echo "Run: git push && gh pr create"
  exit 0
fi

# Only continue for complex analysis

Pattern 2: Template-Driven Assessment

# Use project templates as source of truth
if [ -f "CONTRIBUTING.md" ]; then
  # Extract checklist from CONTRIBUTING.md
  grep -E "^- \[ \]" CONTRIBUTING.md > /tmp/checklist.txt

  # Validate against checklist (not deep analysis)
  while IFS= read -r item; do
    # Check each item (Bash commands, not file reads)
    echo "Validating: $item"
  done < /tmp/checklist.txt
fi

Pattern 3: Git Analysis Over File Analysis

# Pattern detection from history
git log --all --format="%s" | head -50 | \
  grep -oE "^(feat|fix|docs|test|refactor|chore)" | \
  sort | uniq -c | sort -rn

# Branch naming pattern
git branch -r | grep -oE "(feature|fix|hotfix)/" | \
  sort | uniq -c

# Commit message length
git log -n 20 --format="%s" | awk '{print length}' | \
  awk '{sum+=$1; count++} END {print sum/count}'

Pattern 4: Validation Without Deep Reads

# Check existence, not content
checks=(
  ".github/workflows/ci.yml:CI configured"
  ".github/PULL_REQUEST_TEMPLATE.md:PR template"
  ".git/hooks/pre-commit:Pre-commit hooks"
  "CHANGELOG.md:Changelog maintained"
  "LICENSE:License present"
)

for check in "${checks[@]}"; do
  file="${check%%:*}"
  desc="${check##*:}"
  [ -f "$file" ] && echo "✓ $desc"
done

Caching Strategy

Cache Location: .claude/cache/contributing/

Cached Data:

• metadata.json - Project contribution metadata
• guidelines.md - Extracted from CONTRIBUTING.md
• pr_template.md - PR template content
• workflow.txt - Detected git workflow
• checks.json - Required validation checks
• patterns.json - Git commit/branch patterns

Cache Invalidation:

• When .github/ directory changes
• When CONTRIBUTING.md modified
• When package.json modified (script changes)
• Manual: Every 7 days

Cache Sharing:

• Shared with /commit - Commit conventions
• Shared with /review - Code standards
• Shared with /test - Test requirements
• Shared with /understand - Project structure

Expected Results

Before Optimization:

• Average: 3,000-5,000 tokens per run
• Full analysis every time
• Multiple file reads
• Deep content analysis

After Optimization:

• Quick check: 500-800 tokens (80% reduction)
• Standard: 1,000-1,500 tokens (65% reduction)
• Full analysis: 1,500-1,800 tokens (60% reduction)
• Average: 1,000-1,800 tokens (65% reduction)

Performance Gains:

• 85% of cases: Early exit after pre-flight (500 tokens)
• 10% of cases: Template-based assessment (1,000 tokens)
• 5% of cases: Full analysis needed (1,800 tokens)
• Weighted average: 65% reduction achieved

Optimization Status: ✅ Optimized (Phase 2 Batch 3B, 2026-01-26)

Based on this framework, I'll begin by detecting your context:

Context Detection First: Let me understand what situation you're in:

1. Active Session Context (you've been implementing):

   • Read CLAUDE.md for session goals and work done
   • Analyze ALL files modified during session
   • Check if tests were run and passed
   • Review commits made during session
   • Understand the complete scope of changes

2. Post-Implementation Context (feature complete):

   • Detect completed features/fixes
   • Check test coverage for new code
   • Verify documentation was updated
   • Analyze code quality and standards

3. Mid-Development Context (work in progress):

   • Identify what's done vs. TODO
   • Check partial implementations
   • Assess readiness for contribution

4. Cold Start Context (no recent work):

   • Analyze existing uncommitted changes
   • Review branch differences from main
   • Understand project state

Smart Context Analysis: Based on what I find, I'll adapt my approach:

• Session work: Package all session changes properly
• Multiple features: Suggest splitting into PRs
• Bug fixes: Fast-track simple contributions
• Major changes: Full contribution workflow

Phase 0: MANDATORY Pre-Flight Checks BEFORE anything else, I MUST verify:

• Build passes: Run project's build command
• Tests pass: All tests must be green
• Lint passes: No linting errors
• Type check passes: If TypeScript/Flow/etc
• Format check: Code properly formatted

If ANY check fails → STOP and fix first!

Phase 1: Deep Context Analysis I'll understand EVERYTHING about your situation:

A. Session Context (if you've been working):

• Read CLAUDE.md for complete session history
• Analyze ALL files changed during session
• Check test results from /test runs
• Review any /review or /security-scan results
• Understand features implemented

B. Cold Start Context (running standalone):

• Run /understand to map entire codebase
• Analyze all local commits vs remote
• Detect uncommitted changes
• Compare fork with upstream (if applicable)
• Identify what makes your version unique

C. Implementation Context:

• Multiple features completed → Smart PR splitting
• Bug fixes done → Link to issue tracker
• Tests added → Update coverage reports
• Docs updated → Ensure consistency

Phase 2: Project Type Detection I'll identify what kind of project this is:

• Open Source: Full CONTRIBUTING.md compliance needed
• Company/Team: Internal standards and workflows
• Personal: Your own conventions
• Fork: Upstream project requirements
• Client Work: Specific deliverables

Phase 3: Repository Standards Analysis Based on project type, I'll examine:

• Read CONTRIBUTING.md, README.md, CHANGELOG.md, LICENSE files
• Analyze .github workflows, issue templates, PR templates
• Check code patterns, naming conventions, architectural decisions
• Review commit history for maintainer preferences and patterns
• Detect specific requirements (DCO, CLA, tests, docs)

Phase 4: Smart Comparison I'll compare your work against requirements:

• Feature Completeness: All acceptance criteria met?
• Test Coverage: New code properly tested?
• Documentation: Features documented?
• Code Standards: Follows project style?
• Breaking Changes: Handled properly?

Phase 5: Context-Aware Action Plan Based on your specific situation:

If you just finished a session:

• Package all session work into coherent PR(s)
• Generate comprehensive test report
• Create session-based PR description
• Link to issues mentioned in session

If you have multiple features:

• Suggest logical PR splits
• Order PRs by dependencies
• Create issue tracking for each

If contributing to open source:

• Full CONTRIBUTING.md compliance check
• DCO/CLA signature verification
• Community guidelines adherence
• Issue linkage and proper labels

Phase 6: Intelligent Remote Repository Scanning I'll do a DEEP scan of the remote repository to maximize PR acceptance:

Automatic Issue Discovery & Linking: When you've made changes, I'll search for:

• Bug Reports: "error", "bug", "broken" + your fixed files
• Feature Requests: "feature", "enhancement" + your implementations
• Improvements: "performance", "refactor" + your optimizations
• Documentation: "docs", "readme" + your doc updates

Smart Matching Algorithm: For each change you made, I'll:

1. Extract keywords from your code changes
2. Search remote issues for matches
3. Analyze issue descriptions and comments
4. Find the BEST matches to link

Proactive Issue Creation: If NO matching issues exist, I'll:

1. Detect what type of change (bug fix, feature, etc.)
2. Use project's issue templates
3. Create issues in project's style (NO EMOJIS):
   • Bug: Steps to reproduce, expected vs actual
   • Feature: User story, benefits, implementation
   • Enhancement: Current vs improved behavior
   • Professional tone: Direct, factual, concise
4. Follow project's labeling conventions

Git Workflow Detection: I'll analyze the project's workflow:

• Git Flow: feature/, hotfix/, release/*
• GitHub Flow: feature branches → main
• GitLab Flow: environment branches
• Custom: Detect from existing PRs

Smart PR Strategy: Based on what I find:

• Issues exist: Link with "Fixes #X", "Closes #Y"
• No issues: Create them first, then link
• Multiple issues: One PR per issue or grouped logically
• Discussion threads: Reference with "See #Z"

PR/Issue Style:

• Concise titles: "Fix auth validation bug" not "Fixed the authentication validation bug that was causing issues"
• Bullet points: Use lists, not paragraphs
• No emojis: Professional tone only
• Direct language: "This PR fixes X" not "I hope this PR might help with X"
• Match project tone: Analyze existing PRs for style

Phase 7: Smart Decision Tree When I find multiple items, I'll create a todo list with prioritized actions:

• Critical items that could block PR acceptance
• Recommended improvements for better approval chances
• Optional enhancements based on project patterns

I'll provide specific guidance:

• Exact files to update and how
• Required documentation changes
• Testing strategies that fit the project
• PR description template following project standards

Context-Based Options: "How should we proceed?"

For session work:

• "Package session work into PR" - I'll create PR from all session changes
• "Create issues for TODOs" - Track remaining work
• "Split into multiple PRs" - If you did multiple features

For open source contributions:

• "Full compliance check & PR" - Complete CONTRIBUTING workflow
• "Create tracking issues first" - For complex features
• "Quick fix PR" - For simple bug fixes

For team/company projects:

• "Follow internal process" - Your team's specific workflow
• "Create feature branch PR" - Standard git flow
• "Deploy to staging first" - If required

Smart PR Creation: Based on context, I'll:

• Use session summary for PR description
• Include test results automatically
• Link to related issues/discussions
• Follow project's PR template exactly
• Add appropriate labels and reviewers

Automated Workflow Options:

Option 1: "Full Auto-Deploy with Issue Management":

# I'll automatically:
1. RUN ALL CHECKS FIRST:
   - Build must pass
   - All tests must pass
   - Lint must pass
   - Type check must pass
2. Only if ALL pass, then:
3. Scan remote for ALL related issues
4. Create missing issues for your changes
5. Update CHANGELOG.md 
6. Create proper branch (feature/fix/etc)
7. Push changes
8. Create PR with:
   - Links to all related issues
   - "Fixes #123" for bugs
   - "Implements #456" for features
   - Perfect description following template
9. Add labels and request reviewers

Option 2: "Prepare Everything" (review before push):

# I'll prepare but let you review:
1. Stage all changes properly
2. Generate PR description
3. Create issue links
4. Show you everything before push

Option 3: "Just Analyze" (see what needs doing):

# I'll analyze and report:
1. What's ready vs. what's missing
2. Compliance gaps
3. Suggested improvements
4. Issue opportunities

Fork-Specific Intelligence:

• Compare with upstream changes
• Suggest rebasing if needed
• Identify conflicts early
• Format for upstream acceptance

Intelligent Session Analysis Example: If you've been working and made changes:

You: /contributing

Me: Analyzing your session...
- Found: You fixed auth bug in UserService.js
- Found: You added rate limiting feature
- Found: You improved performance in API

Scanning remote repository...
- Issue #45: "Auth fails randomly" → Your fix addresses this!
- Issue #67: "Need rate limiting" → You implemented this!
- No issue for performance improvement → I'll create one

Options:
1. Create issue for performance + 3 PRs (one per issue)
2. Create issue + 1 PR fixing all three
3. Just prepare everything for review

Post-Implementation Auto-Actions:

• Scan remote for linkable issues
• Create missing issues automatically
• Run /format on all changed files
• Run /test to ensure everything passes
• Run /docs to update documentation
• Create PR with maximum context

Important: I will NEVER:

• Add "Created by Claude" or any AI attribution to issues/PRs
• Include "Generated with Claude Code" in descriptions
• Modify repository settings or permissions
• Add any AI/assistant signatures or watermarks
• Use emojis in PRs, issues, or commit messages
• Be unnecessarily verbose in descriptions
• Add flowery language or excessive explanations
• PUSH TO GITHUB WITHOUT PASSING TESTS
• CREATE PR IF BUILD IS BROKEN
• SUBMIT CODE WITH LINT ERRORS

Professional Standards:

• Be concise: Get to the point quickly
• Be objective: Facts over feelings
• Follow project style: Match existing PR/issue tone
• No emojis: Keep it professional
• Clear and direct: What changed and why
• Practical focus: Implementation details that matter

This ensures maximum probability of PR acceptance by following all project standards and community expectations while avoiding duplicate work.