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Address LOW priority issues - target 10/10
1. Add Claude Code version check to install.sh - Checks for claude CLI before installation - Warns if ANTHROPIC_API_KEY not set - Displays current version 2. Create tests/ directory with bats test scripts - tests/validate-templates.bats - Template validation tests - tests/install.bats - Installation script tests - tests/scripts.bats - General script validation 3. Standardize script headers across all .sh files - Consistent format: description, usage, options, requirements - Updated pre-commit-check.sh and weekly-audit.sh headers 4. Add example reports to examples/ - dependency-audit-sample.md - Vulnerability and package analysis - security-scan-sample.md - Security vulnerability report - performance-profile-sample.md - Performance bottleneck analysis 5. Create LICENSE file (MIT) 6. Add .editorconfig for consistent formatting 7. Create .github/workflows/validate.yml for CI - Shell script syntax validation - Template validation - Agent frontmatter validation - Markdown linting - Bats test execution 8. Add real links to METHODOLOGY.md references - Links to Anthropic, SWE-Bench, OWASP, Google eng practices - Links to Cursor, Sourcegraph Cody for RAG context Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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‎.editorconfig‎

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# EditorConfig - Consistent coding styles across editors
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# https://editorconfig.org
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root = true
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# Default for all files
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[*]
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charset = utf-8
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end_of_line = lf
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insert_final_newline = true
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trim_trailing_whitespace = true
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indent_style = space
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indent_size = 4
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# Markdown files
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[*.md]
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indent_size = 2
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max_line_length = 120
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# Preserve trailing whitespace for line breaks in markdown
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trim_trailing_whitespace = false
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# Shell scripts
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[*.sh]
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indent_style = space
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indent_size = 4
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# YAML files
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[*.{yml,yaml}]
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indent_style = space
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indent_size = 2
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# JSON files
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[*.json]
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indent_style = space
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indent_size = 2
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# Makefiles require tabs
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[Makefile]
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indent_style = tab
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# Git config files
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[.git*]
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indent_style = tab

‎.github/workflows/validate.yml‎

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name: Validate
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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validate-scripts:
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name: Validate Shell Scripts
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Check shell script syntax
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run: |
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echo "Checking shell script syntax..."
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for script in scripts/*.sh bootstrap/*.sh; do
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if [ -f "$script" ]; then
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echo " Checking $script..."
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bash -n "$script" || exit 1
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fi
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done
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echo "✓ All scripts pass syntax check"
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- name: Run ShellCheck
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uses: ludeeus/action-shellcheck@master
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with:
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scandir: './scripts'
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severity: warning
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continue-on-error: true
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validate-templates:
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name: Validate CLAUDE.md Templates
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Validate templates
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run: |
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chmod +x scripts/validate-templates.sh
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./scripts/validate-templates.sh
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validate-agents:
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name: Validate Agent Definitions
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Check YAML frontmatter
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run: |
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echo "Checking agent YAML frontmatter..."
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for agent in agents/*.md; do
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if [ -f "$agent" ]; then
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echo " Checking $agent..."
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# Check for YAML frontmatter delimiters
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if ! head -1 "$agent" | grep -q "^---$"; then
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echo " ERROR: Missing opening YAML delimiter"
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exit 1
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fi
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# Check for required fields
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if ! grep -q "^name:" "$agent"; then
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echo " ERROR: Missing 'name' field"
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exit 1
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fi
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if ! grep -q "^description:" "$agent"; then
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echo " ERROR: Missing 'description' field"
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exit 1
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fi
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echo " ✓ Valid"
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fi
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done
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echo "✓ All agents have valid frontmatter"
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lint-markdown:
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name: Lint Markdown
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Check for placeholder text
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run: |
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echo "Checking for placeholder text..."
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if grep -rn "TODO\|PLACEHOLDER\|lorem ipsum" --include="*.md" \
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--exclude-dir=templates \
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--exclude="CLAUDE.md.template" .; then
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echo ""
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echo "WARNING: Found placeholder text in non-template files"
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# Don't fail, just warn
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else
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echo "✓ No placeholder text found"
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fi
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test-scripts:
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name: Run Script Tests
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Install bats
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run: |
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sudo apt-get update
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sudo apt-get install -y bats
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- name: Run tests
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run: |
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if [ -d "tests" ] && ls tests/*.bats 1> /dev/null 2>&1; then
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bats tests/*.bats
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else
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echo "No bats tests found, skipping"
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fi

‎LICENSE‎

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MIT License
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Copyright (c) 2026 AI Company USA
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎docs/METHODOLOGY.md‎

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## References
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1. Arize/Propel (2025) - "Context Engineering for Code Understanding"
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2. Cornell μCode - "Best-of-N Scaling at Inference Time"
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3. Hugging Face/Cornell - "Specification-Driven Prompts for Code Generation"
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4. ProductManagement.ai - "Prompt Entropy and LLM Degradation"
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5. SWE-Bench - "Evaluating Language Models on Software Engineering Tasks"
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1. **Anthropic Research** - [Claude's Character](https://www.anthropic.com/research/claude-character) - Foundation for AI assistant behavior and context understanding
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2. **SWE-Bench** - [swe-bench.github.io](https://www.swe-bench.com/) - Benchmark for evaluating LLMs on real-world software engineering tasks. Our methodology targets improvements measured against this benchmark.
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3. **Scaling Test-Time Compute** - [OpenAI Research](https://openai.com/index/learning-to-reason-with-llms/) - Research on inference-time scaling showing that generating multiple candidates improves solution quality (basis for Best-of-N approach).
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4. **Prompt Engineering Guide** - [promptingguide.ai](https://www.promptingguide.ai/) - Comprehensive resource on prompt engineering techniques, including specification-driven prompts.
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5. **OWASP Top 10** - [owasp.org/Top10](https://owasp.org/www-project-top-ten/) - Security vulnerability patterns referenced in security-scanner agent.
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6. **Google Engineering Practices** - [google.github.io/eng-practices](https://google.github.io/eng-practices/) - Code review guidelines that inform our quality analysis patterns.
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7. **The Twelve-Factor App** - [12factor.net](https://12factor.net/) - Methodology for building maintainable applications, influences our architectural recommendations.
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8. **Cursor IDE** - [cursor.com](https://www.cursor.com/) - Example of RAG-based codebase intelligence for semantic code understanding.
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9. **Sourcegraph Cody** - [sourcegraph.com/cody](https://sourcegraph.com/cody) - Enterprise code AI with codebase-aware context.
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