diff --git a/BOOKMARKS.md b/BOOKMARKS.md
new file mode 100644
index 00000000..7b4fc922
--- /dev/null
+++ b/BOOKMARKS.md
@@ -0,0 +1,109 @@
+# AgentReady Bookmarks
+
+Quick navigation to detailed documentation for specific tasks.
+
+## Core Documentation
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| User Guide | `README.md` | Installation, basic usage, CLI examples |
+| Full User Guide | `docs/user-guide.md` | Comprehensive user documentation |
+| Developer Guide | `docs/developer-guide.md` | In-depth development patterns |
+| API Reference | `docs/api-reference.md` | Module and class documentation |
+| Attributes | `docs/attributes.md` | All 25 assessed attributes explained |
+
+## Assessors
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| All Assessors | `src/agentready/assessors/__init__.py:49-93` | See full assessor list |
+| Base Class | `src/agentready/assessors/base.py` | Creating new assessors |
+| Documentation | `src/agentready/assessors/documentation.py` | CLAUDE.md, README assessors |
+| Code Quality | `src/agentready/assessors/code_quality.py` | Type annotations, complexity |
+| Testing | `src/agentready/assessors/testing.py` | Coverage, pre-commit hooks |
+| Security | `src/agentready/assessors/security.py` | Dependency vulnerabilities |
+
+## Scoring & Weights
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Default Weights | `src/agentready/data/default-weights.yaml` | Tier weight configuration |
+| Scorer Logic | `src/agentready/services/scorer.py` | Score calculation algorithm |
+| Research Report | `src/agentready/data/RESEARCH_REPORT.md` | Evidence for attribute selection |
+
+## CLI Commands
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Main Entry | `src/agentready/cli/main.py` | Core CLI orchestration |
+| Bootstrap | `src/agentready/cli/bootstrap.py` | Infrastructure setup command |
+| Align | `src/agentready/cli/align.py` | Automated remediation command |
+| Benchmark | `src/agentready/cli/benchmark.py` | Terminal-Bench integration |
+| Learn | `src/agentready/cli/learn.py` | LLM-powered skill extraction |
+
+## Benchmarks & Experiments
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Harbor Guide | `docs/harbor-comparison-guide.md` | A/B testing with Terminal-Bench |
+| Harbor Models | `src/agentready/models/harbor.py` | HarborTaskResult, HarborComparison |
+| Harbor Services | `src/agentready/services/harbor/` | Runner, comparer, result parser |
+| SWE-bench | `experiments/README.md` | Validation workflow |
+
+## Reports & Templates
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| HTML Reporter | `src/agentready/reporters/html.py` | HTML report generation |
+| Markdown Reporter | `src/agentready/reporters/markdown.py` | Markdown report generation |
+| HTML Template | `src/agentready/templates/report.html.j2` | Jinja2 HTML template (73KB) |
+| Example Reports | `examples/self-assessment/` | Sample output files |
+
+## Schemas & Contracts
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Assessment Schema | `specs/001-agentready-scorer/contracts/assessment-schema.json` | JSON validation |
+| Research Schema | `specs/001-agentready-scorer/contracts/research-report-schema.md` | Research format |
+| Report Schemas | `specs/001-agentready-scorer/contracts/report-*.md` | HTML/Markdown format |
+
+## CI/CD & Automation
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Main CI | `.github/workflows/ci.yml` | Test/lint pipeline |
+| Release | `.github/workflows/release.yml` | Publishing workflow |
+| Self-Assessment | `.github/workflows/agentready-assessment.yml` | Auto-assessment |
+| PR Review | `.github/workflows/pr-review.yml` | Automated review |
+| Claude Integration | `.github/CLAUDE_INTEGRATION.md` | Bot configuration |
+
+## Testing
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Unit Tests | `tests/unit/` | Assessor and model tests |
+| Integration Tests | `tests/integration/` | End-to-end tests |
+| E2E Tests | `tests/e2e/` | Full workflow tests |
+| Fixtures | `tests/fixtures/` | Test data |
+
+## LLM Integration
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| LLM Cache | `src/agentready/services/llm_cache.py` | Response caching (7-day TTL) |
+| LLM Enricher | `src/agentready/learners/llm_enricher.py` | Claude API integration |
+| Prompt Templates | `src/agentready/prompts/` | LLM prompt .md files |
+| Skill Generator | `src/agentready/learners/skill_generator.py` | SKILL.md generation |
+
+## Project Planning
+
+| Topic | Location | When to Use |
+|-------|----------|-------------|
+| Backlog | `BACKLOG.md` | Future features |
+| Changelog | `CHANGELOG.md` | Release history |
+| Feature Specs | `specs/` | Design documents |
+| Cold-Start Prompts | `plans/` (gitignored) | Agent handoff prompts |
+
+---
+
+*Use `Ctrl+F` or `Cmd+F` to search this file for keywords.*
diff --git a/CLAUDE.md b/CLAUDE.md
index e80b2a84..2a5714d4 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -1,456 +1,132 @@
-# AgentReady - Repository Quality Assessment Tool
+# AgentReady
 
-**Purpose**: Assess repositories against agent-ready best practices and generate actionable reports.
+Assess repositories against evidence-based attributes for AI-assisted development readiness.
 
-**Last Updated**: 2026-03-05
+## Quick Reference
 
----
-
-## Overview
+| Item | Value |
+|------|-------|
+| **Version** | 2.29.6 |
+| **Python** | >=3.12 |
+| **Entry Point** | `agentready.cli.main:cli` |
+| **Self-Score** | 80.0/100 (Gold) |
+| **Test Coverage** | 37% (target: >80%) |
 
-AgentReady is a Python CLI tool that evaluates repositories against a comprehensive set of carefully researched attributes that make codebases more effective for AI-assisted development. It generates interactive HTML reports, version-control friendly Markdown reports, and machine-readable JSON output.
+## Commands
 
-**Current Status**: v2.29.6 - Core assessment engine complete, most essential assessors implemented, LLM-powered learning, research report management
-
-**Self-Assessment Score**: 80.0/100 (Gold) - See `examples/self-assessment/`
+```bash
+# Core
+agentready assess <repo>           # Assess repository
+agentready bootstrap <repo>        # Setup agent-ready infrastructure
+agentready align <repo>            # Automated remediation
 
-**For User Documentation**: See `README.md` for installation, usage examples, and feature tutorials.
+# Development
+pytest                             # Run tests
+pytest --cov=src/agentready        # With coverage
+black . && isort . && ruff check . # Lint
 
----
+# Benchmarks (requires: uv tool install harbor)
+agentready harbor compare -t task1 -t task2
+```
 
 ## Architecture
 
-### Core Components
-
 ```
 src/agentready/
-├── models/          # Data models (Repository, Attribute, Finding, Assessment)
-├── services/        # Scanner orchestration and language detection
-│   ├── llm_cache.py         # LLM response caching (7-day TTL)
-│   ├── research_loader.py   # Research report loading and validation
-│   └── research_formatter.py # Research report formatting utilities
-├── assessors/       # Attribute assessment implementations
-│   ├── base.py      # BaseAssessor abstract class
-│   ├── documentation.py   # CLAUDE.md, README assessors
-│   ├── code_quality.py    # Type annotations, complexity
-│   ├── testing.py         # Test coverage, pre-commit hooks
-│   ├── structure.py       # Standard layout, gitignore
-│   ├── repomix.py         # Repomix configuration assessor
-│   └── stub_assessors.py  # Remaining assessors in development
-├── learners/        # Pattern extraction and LLM enrichment
-│   ├── pattern_extractor.py  # Heuristic skill extraction
-│   ├── skill_generator.py    # SKILL.md generation
-│   ├── code_sampler.py       # Repository code sampling
-│   ├── llm_enricher.py       # Claude API integration
-│   └── prompt_templates.py   # LLM prompt engineering
-├── reporters/       # Report generation (HTML, Markdown, JSON)
-│   ├── html.py      # Interactive HTML with Jinja2
-│   └── markdown.py  # GitHub-Flavored Markdown
-├── prompts/        # LLM prompt .md templates; load_prompt(name) from loader.py
-├── templates/       # Jinja2 templates
-│   └── report.html.j2  # Self-contained HTML report (73KB)
-└── cli/             # Click-based CLI
-    ├── main.py      # assess, research-version, generate-config commands
-    ├── learn.py     # Continuous learning loop with LLM enrichment
-    └── research.py  # Research report management commands
-```
-
-### Data Flow
-
-```
-Repository → Scanner → Assessors → Findings → Assessment → Reporters → Reports
-                ↓
-         Language Detection
-         (git ls-files)
-```
-
-### Scoring Algorithm
-
-1. **Tier-Based Weighting** (50/30/15/5 distribution):
-   - Tier 1 (Essential): 50% of total score
-   - Tier 2 (Critical): 30% of total score
-   - Tier 3 (Important): 15% of total score
-   - Tier 4 (Advanced): 5% of total score
-
-2. **Attribute Scoring**: Each attribute returns 0-100 score
-3. **Weighted Aggregation**: `final_score = Σ(attribute_score × weight)`
-4. **Certification Levels**:
-   - Platinum: 90-100
-   - Gold: 75-89
-   - Silver: 60-74
-   - Bronze: 40-59
-   - Needs Improvement: 0-39
-
----
-
-## Development
-
-### Setup
-
-```bash
-# Create virtual environment
-uv venv
-source .venv/bin/activate
-
-# Install dependencies
-uv pip install -e .
-
-# Install development tools
-uv pip install pytest black isort ruff
-```
-
-### Running Tests
-
-```bash
-# Run all tests
-pytest
-
-# Run with coverage
-pytest --cov=src/agentready --cov-report=html
-
-# Run specific test file
-pytest tests/unit/test_models.py -v
+├── assessors/    # 25 attribute evaluators (see assessors/__init__.py:49-93)
+├── cli/          # Click commands with LazyGroup optimization
+├── data/         # default-weights.yaml, RESEARCH_REPORT.md
+├── fixers/       # Automated remediation strategies
+├── github/       # PR review formatting
+├── learners/     # LLM-powered pattern extraction
+├── models/       # Repository, Assessment, Finding, Attribute
+├── prompts/      # LLM prompt templates
+├── reporters/    # HTML, Markdown, JSON output
+├── services/     # Scanner orchestration, scoring, caching
+├── templates/    # Jinja2 HTML templates
+└── utils/        # preflight, privacy, security, subprocess
 ```
 
-**Current Coverage**: 37% (focused on core logic, targeting >80%)
-
-### Code Quality
+**Data Flow**: Repository -> Scanner -> Assessors -> Findings -> Scorer -> Reporters
 
-```bash
-# Pre-push linting workflow
-black src/ tests/ && isort src/ tests/ && ruff check src/ tests/
-```
+## Scoring
 
-### Cold-Start Prompts Pattern
+**Tier weights** (from `data/default-weights.yaml:6-9`):
+- Tier 1 (Essential): 55%
+- Tier 2 (Critical): 27%
+- Tier 3 (Important): 15%
+- Tier 4 (Advanced): 3%
 
-Enable context-free agent handoff by creating self-contained prompts in `plans/` (gitignored).
+**Certification**: Platinum (90+), Gold (75-89), Silver (60-74), Bronze (40-59)
 
-**Include**: Requirements, implementation approach, code patterns, test guidance, dependencies
+## Adding Assessors
 
-**Workflow**: Planning → `plans/feature-name.md` → GitHub issue (copy prompt) → Future agent implements
+1. Create class inheriting `BaseAssessor` (`assessors/base.py`)
+2. Implement `attribute_id` property and `assess(repository)` method
+3. Register in `assessors/__init__.py:create_all_assessors()`
+4. Add tests in `tests/unit/test_assessors_*.py`
 
-**Benefits**: Asynchronous development, complete context without chat history, standardized knowledge transfer
+**Reference implementations**:
+- Simple: `CLAUDEmdAssessor` at `assessors/documentation.py`
+- Complex: `TypeAnnotationsAssessor` at `assessors/code_quality.py`
+- Conditional: `ContainerSetupAssessor` at `assessors/containers.py`
 
-### Adding New Assessors
+## Key Patterns
 
-1. **Expand a stub assessor** in `src/agentready/assessors/stub_assessors.py`
-2. **Create new assessor class** inheriting from `BaseAssessor`
-3. **Implement required methods**:
-   - `attribute_id` property
-   - `assess(repository)` method
-   - `is_applicable(repository)` method (optional)
-4. **Add tests** in `tests/unit/test_assessors_*.py`
-5. **Register** in scanner's assessor list
+**Proportional scoring**: Use `calculate_proportional_score()` for partial compliance
 
-**Example**:
+**Graceful degradation**: Return "skipped" if tools missing, never crash
 
+**Finding creation**:
 ```python
-class MyAssessor(BaseAssessor):
-    @property
-    def attribute_id(self) -> str:
-        return "my_attribute_id"
-
-    def assess(self, repository: Repository) -> Finding:
-        # Implement assessment logic
-        if condition_met:
-            return Finding.create_pass(self.attribute, ...)
-        else:
-            return Finding.create_fail(self.attribute, ...)
+Finding.create_pass(self.attribute, evidence="...", details="...")
+Finding.create_fail(self.attribute, evidence="...", remediation="...")
 ```
 
-**Reference Implementations**:
-
-- Simple: `CLAUDEmdAssessor` (file existence check)
-- Complex: `TypeAnnotationsAssessor` (proportional scoring)
-- Language-aware: `TestCoverageAssessor` (conditional logic)
-
----
-
-## Project Structure
-
-```
-agentready/
-├── src/agentready/          # Source code
-├── tests/                   # Test suite
-│   ├── unit/               # Unit tests
-│   └── integration/        # End-to-end tests
-├── examples/               # Example reports
-│   └── self-assessment/    # AgentReady's own assessment
-├── specs/                  # Feature specifications
-├── plans/                  # Cold-start prompts (gitignored)
-├── experiments/            # SWE-bench validation studies
-├── contracts/              # Data schemas and validation rules
-├── pyproject.toml          # Python package configuration
-├── CLAUDE.md              # This file (developer guide)
-├── README.md              # User-facing documentation
-├── BACKLOG.md             # Future features and enhancements
-└── GITHUB_ISSUES.md       # GitHub-ready issue templates
-```
-
----
-
-## Harbor Benchmark Comparison
-
-Empirically measure Claude Code performance impact of `.claude/agents/doubleagent.md` using Harbor's Terminal-Bench.
-
-The Harbor comparison feature automates A/B testing by running Terminal-Bench tasks with/without agent files, calculating deltas and statistical significance, and generating comprehensive reports (JSON, Markdown, HTML).
-
-### Quick Start
-
-```bash
-# Install Harbor
-uv tool install harbor
-
-# Run comparison (3 tasks, ~30-60 min)
-agentready harbor compare \
-  -t adaptive-rejection-sampler \
-  -t async-http-client \
-  -t terminal-file-browser \
-  --verbose \
-  --open-dashboard
-```
-
-### Key Metrics
-
-- **Success Rate**: Percentage of tasks completed successfully
-- **Duration**: Average time to complete tasks
-- **Statistical Significance**: T-tests (p<0.05) and Cohen's d effect sizes
-- **Per-Task Impact**: Individual task improvements/regressions
-
-### Output Files
-
-Results stored in `.agentready/harbor_comparisons/` (gitignored):
-
-- **JSON**: Machine-readable comparison data
-- **Markdown**: GitHub-friendly report (commit this for PRs)
-- **HTML**: Interactive dashboard with Chart.js visualizations
-
-### CLI Commands
-
-**Compare**:
-
-```bash
-agentready harbor compare -t task1 -t task2 [--verbose] [--open-dashboard]
-```
-
-**List comparisons**:
-
-```bash
-agentready harbor list
-```
-
-**View comparison**:
-
-```bash
-agentready harbor view .agentready/harbor_comparisons/comparison_latest.json
-```
-
-### Architecture
-
-| Component | Location | Purpose |
-|-----------|----------|---------|
-| **Data Models** | `models/harbor.py` | HarborTaskResult, HarborRunMetrics, HarborComparison |
-| **Services** | `services/harbor/` | HarborRunner, AgentFileToggler, ResultParser, HarborComparer |
-| **Reporters** | `reporters/` | HarborMarkdownReporter, DashboardGenerator |
-
-### Statistical Analysis
-
-- **Significance**: P-value < 0.05 (t-test) AND Cohen's d effect size (Small: 0.2-0.5, Medium: 0.5-0.8, Large: ≥0.8)
-- **Sample Sizes**: Minimum 3 tasks, Recommended 5-10, Comprehensive 20+
-
-### Documentation
-
-- **User Guide**: `docs/harbor-comparison-guide.md`
-- **Implementation Plan**: `.claude/plans/vivid-knitting-codd.md`
-- **Harbor Docs**: <https://harborframework.com/docs>
-
----
-
-## Technologies
-
-- **Python 3.11+** (only N and N-1 versions supported)
-- **Click** - CLI framework
-- **Jinja2** - HTML template engine
-- **Anthropic** - Claude API client (for LLM enrichment)
-- **Pytest** - Testing framework
-- **Black** - Code formatter
-- **isort** - Import sorter
-- **Ruff** - Fast Python linter
-- **Harbor** - Evaluation framework (optional, for benchmarks)
-
----
-
-## Preflight Checks
-
-AgentReady validates dependencies before running benchmarks:
-
-- **Harbor CLI**: Checked automatically before Terminal-Bench runs
-- **Interactive installation**: Prompts user with `uv tool install harbor` (or `pip install harbor` fallback)
-- **Opt-out**: Use `--skip-preflight` flag to bypass checks for advanced users
-- **Package manager fallback**: Prefers `uv`, falls back to `pip` if `uv` not available
-- **Security**: Uses `safe_subprocess_run()` with 5-minute timeout
-
-**Implementation**:
-
-- Module: `src/agentready/utils/preflight.py`
-- Tests: `tests/unit/utils/test_preflight.py` (100% coverage)
-- Integration: `src/agentready/cli/benchmark.py`
-
-**Usage Examples**:
-
-```bash
-# Normal usage (preflight check runs automatically)
-agentready benchmark --subset smoketest
-
-# Skip preflight (advanced users)
-agentready benchmark --subset smoketest --skip-preflight
-```
-
----
-
-## Contributing
-
-### Workflow
-
-1. **Create feature branch** from `main`
-2. **Implement changes** with tests
-3. **Run linters**: `black . && isort . && ruff check .`
-4. **Run tests**: `pytest`
-5. **Commit** with conventional commit messages
-6. **Push** and create PR
-
-### Conventional Commits
-
-```
-feat: Add new assessor for dependency freshness
-fix: Correct type annotation detection in Python 3.12
-docs: Update CLAUDE.md with architecture details
-test: Add integration test for HTML report generation
-refactor: Extract common assessor logic to base class
-chore: Update dependencies
-```
-
-### Test Requirements
-
-- All new assessors must have unit tests
-- Integration tests for new reporters
-- Maintain >80% coverage for new code
-- All tests must pass before merge
-
----
-
 ## CI/CD
 
-**GitHub Actions**:
+16 GitHub Actions workflows in `.github/workflows/`:
+- `ci.yml` - Tests (Py 3.12/3.13), linting, coverage
+- `release.yml` - Semantic versioning, PyPI publish
+- `agentready-assessment.yml` - Self-assessment on commits
+- `pr-review.yml` - Automated PR review
 
-- Run tests on PR
-- Run linters (black, isort, ruff)
-- Generate coverage report
-- Run AgentReady self-assessment
-- Post assessment results as PR comment
+**Note for agents**: Always run `actionlint` before pushing workflow changes.
 
-**Current**: Manual workflow (tests run locally before push)
-
----
+## Conventions
 
-## Known Issues & Limitations
+**Commits**: `feat:`, `fix:`, `docs:`, `test:`, `refactor:`, `chore:`
 
-1. **Stub Assessors**: 9/31 assessors still return "not_applicable" - need implementation
-2. **No Lock File**: Intentionally excluded for library project (assessed as deliberate choice)
-3. **Test Coverage**: Currently at ~37%, targeting >80% for production readiness
+**Tests**: All new assessors require unit tests. Maintain >80% coverage for new code.
 
----
+**Linting**: Run `black . && isort . && ruff check .` before commits
 
-## Roadmap
+## Key Files
 
-### v2.x - Current Development (In Progress)
+| Purpose | Location |
+|---------|----------|
+| Weight config | `src/agentready/data/default-weights.yaml` |
+| Research report | `src/agentready/data/RESEARCH_REPORT.md` |
+| HTML template | `src/agentready/templates/report.html.j2` |
+| Schemas | `specs/001-agentready-scorer/contracts/` |
+| Issue templates | `.github/ISSUE_TEMPLATE/` |
 
-- **In Progress**: Expand remaining stub assessors
-- **In Progress**: Improve test coverage to >80%
-- **Planned**: Bootstrap command (automated remediation)
-- **Planned**: Align command (automated alignment)
+## Agent Guidelines
 
-### v3.0 - Enterprise Features (Future)
+1. **Read before modifying** - Understand existing assessors first
+2. **Follow patterns** - Use reference implementations above
+3. **Test thoroughly** - Unit tests required for all assessors
+4. **Backwards compatibility** - Schema version bump for model changes
+5. **Rich remediation** - Actionable steps with tools, commands, examples
 
-- Customizable HTML themes with dark/light toggle
-- Organization-wide dashboards
-- Historical trend analysis
-- AI-powered assessors with deeper code analysis
+## Related Docs
 
-See `BACKLOG.md` for complete feature list.
+See `BOOKMARKS.md` for navigation to:
+- Harbor benchmarks guide
+- SWE-bench experiments
+- Research report schema
+- Feature specifications
+- API reference (docs/)
 
 ---
 
-## Notes for Claude Code Agents
-
-**When working on AgentReady**:
-
-1. **Read before modifying**: Always read existing assessors before implementing new ones
-2. **Follow patterns**: Use `CLAUDEmdAssessor` and `READMEAssessor` as reference implementations
-3. **Test thoroughly**: Add unit tests for all new assessors
-4. **Maintain backwards compatibility**: Don't change Assessment model without schema version bump
-5. **Stub assessors first**: Check if attribute already has stub before creating new class
-6. **Proportional scoring**: Use `calculate_proportional_score()` for partial compliance
-7. **Graceful degradation**: Return "skipped" if tools missing, don't crash
-8. **Rich remediation**: Provide actionable steps, tools, commands, examples, citations
-
-**Key Principles**:
-
-- Library-first architecture (no global state)
-- Strategy pattern for assessors (each is independent)
-- Fail gracefully (missing tools → skip, don't crash)
-- User-focused (actionable remediation over theoretical guidance)
-
-**Command Reference**:
-
-- User tutorials → See `README.md`
-- CLI help → Run `agentready --help`
-- SWE-bench experiments → See `experiments/README.md`
-- Research report schema → See `contracts/research-report-schema.md`
-
-### Documentation Workflow
-
-**CRITICAL: Proactive Documentation Agent Usage**
-
-Use the `github-pages-docs` agent for documentation updates after:
-
-| Trigger | Action |
-|---------|--------|
-| New features implemented | Update user guide, developer guide, API reference, examples |
-| Source-of-truth files modified | Cascade updates: CLAUDE.md → developer-guide.md, attributes.md → attributes.md |
-| Bugs fixed or issues addressed | Update troubleshooting, known issues, migration guides |
-| Project status changes | Update certification levels, versions, roadmap, milestones |
-
-**Documentation Sources of Truth** (priority order):
-
-1. CLAUDE.md - Project guide
-2. RESEARCH_REPORT.md - Research report
-3. contracts/ - Schemas and validation
-4. specs/ - Feature specifications
-5. Source code - Actual implementation
-
-**Automation**: Manual trigger via `.github/workflows/update-docs.yml` (workflow_dispatch)
-
----
-
-## Related Documents
-
-- **.github/CLAUDE_INTEGRATION.md** - Dual Claude integration guide (automated + interactive)
-- **BACKLOG.md** - Future features and enhancements
-- **GITHUB_ISSUES.md** - GitHub-ready issue templates
-- **README.md** - User-facing documentation
-- **specs/** - Feature specifications and design documents
-- **experiments/README.md** - SWE-bench validation workflow
-- **examples/self-assessment/** - AgentReady's own assessment (80.0/100 Gold)
-
----
-
-**Last Updated**: 2026-03-05 by Jeremy Eder
-**AgentReady Version**: 2.29.6
-**Self-Assessment**: 80.0/100 (Gold) ✨
-
-### GitHub Actions Guidelines
-
-- **ALWAYS run actionlint and fix any issues before pushing changes to GitHub Actions workflows**
-- All workflows must pass actionlint validation with zero errors/warnings
-- Use proper shell quoting and combined redirects for efficiency
diff --git a/src/agentready/data/default-weights.yaml b/src/agentready/data/default-weights.yaml
index f2bae7a4..7ac1631c 100644
--- a/src/agentready/data/default-weights.yaml
+++ b/src/agentready/data/default-weights.yaml
@@ -1,6 +1,6 @@
 # Default Tier-Based Weight Distribution
 #
-# This file defines the default weights for all 23 attributes (updated from 25).
+# This file defines the default weights for all 25 attributes.
 # Weights are based on tier priority from research report:
 #
 # Tier 1 (Essential):  55% total (5×10% + 1×5%, 6 attributes)