skillby jg-chalk-io
moai-docs-validation
Enhanced docs validation with AI-powered features. Enhanced with Context7
Installs: 0
Used in: 1 repos
Updated: 2d ago
$
npx ai-builder add skill jg-chalk-io/moai-docs-validationInstalls to .claude/skills/moai-docs-validation/
# moai-docs-validation
**Docs Validation**
> **Primary Agent**: doc-syncer
> **Secondary Agents**: alfred
> **Version**: 4.0.0
> **Keywords**: docs, validation, auth, cd, test
---
## š Progressive Disclosure
### Level 1: Quick Reference (Core Concepts)
š Content
### Section 1: Validation Framework Overview
Documentation validation ensures content accuracy, completeness, and compliance with MoAI-ADK standards. This skill covers comprehensive validation strategies for:
- **SPEC Compliance**: Verify documentation references valid SPECs and TAG chains
- **Content Accuracy**: Validate code examples, API signatures, configuration patterns
- **Completeness Checking**: Ensure all required sections present and filled
- **Quality Metrics**: Measure readability, coverage, translation quality
- **Multilingual Consistency**: Verify structure and content alignment across languages
**Key Benefits**:
- Catch inaccurate documentation before publication
- Ensure SPEC-documentation traceability
- Maintain quality standards across all documents
- Automate quality gate enforcement
- Enable data-driven documentation improvements
### Section 2: Validation Rules & Standards
#### SPEC Compliance Validation
```yaml
Rules:
- Requirement Coverage: All SPEC requirements addressed in documentation
```
**Example - Good**:
```markdown
# Feature: User Authentication
---
### Level 2: Practical Implementation (Common Patterns)
š Content
### Section 1: Validation Framework Overview
Documentation validation ensures content accuracy, completeness, and compliance with MoAI-ADK standards. This skill covers comprehensive validation strategies for:
- **SPEC Compliance**: Verify documentation references valid SPECs and TAG chains
- **Content Accuracy**: Validate code examples, API signatures, configuration patterns
- **Completeness Checking**: Ensure all required sections present and filled
- **Quality Metrics**: Measure readability, coverage, translation quality
- **Multilingual Consistency**: Verify structure and content alignment across languages
**Key Benefits**:
- Catch inaccurate documentation before publication
- Ensure SPEC-documentation traceability
- Maintain quality standards across all documents
- Automate quality gate enforcement
- Enable data-driven documentation improvements
### Section 2: Validation Rules & Standards
#### SPEC Compliance Validation
```yaml
Rules:
- Requirement Coverage: All SPEC requirements addressed in documentation
```
**Example - Good**:
```markdown
# Feature: User Authentication
---
Implementation
```
**Example - Bad**:
```markdown
# User Authentication
---
How to Authenticate
[No SPEC reference]
[No TAG chain]
[No testing guidance]
```
#### Content Accuracy Validation
```yaml
Rules:
- Code Examples: Tested, executable, syntax-correct
- API Signatures: Match actual implementation
- Parameter Types: Accurate type annotations
- Return Values: Documented behavior matches actual behavior
- Configuration: All config examples work in practice
```
**Validation Pattern**:
```python
def validate_code_examples(self, doc_path: Path) -> List[ValidationError]:
"""Verify code examples are syntactically correct"""
errors = []
# Extract all ```language code blocks
code_blocks = self._extract_code_blocks(doc_path)
for block in code_blocks:
# Verify syntax
syntax_errors = self._check_syntax(block.code, block.language)
if syntax_errors:
errors.append(ValidationError(
file=doc_path,
line=block.line_number,
message=f"Invalid {block.language} syntax",
details=syntax_errors
))
return errors
```
#### Quality Metrics Validation
```yaml
Metrics:
- Readability Score: 60-100 (Flesch-Kincaid readability)
- Coverage: 80%+ of specification requirements
- Code Example Ratio: 1 example per 300 words (target)
- Link Validity: 100% of internal/external links valid
- Translation Completeness: 100% structure alignment across languages
- Image Optimization: All images <500KB, proper alt text
```
**Quality Score Calculation**:
```python
def calculate_quality_score(self, doc_path: Path) -> float:
"""Calculate documentation quality (0-100)"""
scores = {
'spec_compliance': self._check_spec_compliance(doc_path), # 25%
'content_accuracy': self._validate_content_accuracy(doc_path), # 25%
'completeness': self._check_completeness(doc_path), # 20%
'readability': self._calculate_readability(doc_path), # 15%
'formatting': self._check_formatting(doc_path), # 15%
}
weights = {
'spec_compliance': 0.25,
'content_accuracy': 0.25,
'completeness': 0.20,
'readability': 0.15,
'formatting': 0.15,
}
total_score = sum(scores[k] * weights[k] for k in scores)
return round(total_score, 1)
```
### Section 3: TAG Verification System
**TAG Chain Validation**:
```yaml
Valid Chains:
Chain Rules:
- No broken links (referenced TAGs must exist)
```
**Verification Script Pattern**:
```python
class TAGVerifier:
def __init__(self, project_root: Path):
self.project_root = project_root
self.spec_docs = {}
self.test_docs = {}
self.code_refs = {}
self.doc_refs = {}
def verify_chain(self, spec_id: str) -> ValidationResult:
result = ValidationResult(spec_id)
# Check SPEC exists
if spec_id not in self.spec_docs:
return result
# Check TEST exists
if spec_id not in self.test_docs:
# Check CODE references
if spec_id not in self.code_refs:
# Check DOC exists
if spec_id not in self.doc_refs:
return result
```
### Section 4: Multilingual Validation
**Translation Consistency Checks**:
```python
class MultilingualValidator:
def validate_structure_consistency(self) -> List[str]:
"""Ensure all languages have same document structure"""
issues = []
# Get Korean file structure (source)
ko_structure = self._get_file_structure("docs/src/ko")
# Compare with other languages
for lang in ["en", "ja", "zh"]:
lang_structure = self._get_file_structure(f"docs/src/{lang}")
if ko_structure != lang_structure:
missing = set(ko_structure) - set(lang_structure)
extra = set(lang_structure) - set(ko_structure)
if missing:
issues.append(f"[{lang}] Missing files: {missing}")
if extra:
issues.append(f"[{lang}] Extra files: {extra}")
return issues
def validate_translation_quality(self, lang: str) -> float:
"""Score translation completeness (0-100)"""
ko_files = set(self._list_files("docs/src/ko", "*.md"))
lang_files = set(self._list_files(f"docs/src/{lang}", "*.md"))
translated = len(ko_files & lang_files)
translation_ratio = (translated / len(ko_files)) * 100
return round(translation_ratio, 1)
```
### Section 5: Automation & CI/CD Integration
**GitHub Actions Integration Pattern**:
```bash
# Pre-commit validation
python3 .moai/scripts/validate_docs.py --mode pre-commit
# Pull request validation
python3 .moai/scripts/validate_docs.py --mode pr --files-changed
# Full documentation audit
python3 .moai/scripts/validate_docs.py --mode full --report comprehensive
```
**Quality Gate Configuration**:
```yaml
# .moai/quality-gates.yml
documentation:
spec_compliance:
min_score: 90
required: true
action: block_merge
content_accuracy:
min_score: 85
required: true
action: block_merge
link_validity:
broken_links_allowed: 0
required: true
action: block_merge
multilingual_consistency:
max_missing_translations: 0
required: true
action: warning
```
**Automated Reports**:
```python
def generate_validation_report(self, output_format: str = "markdown") -> str:
"""Generate comprehensive validation report"""
report = []
# Summary
report.append("# Documentation Validation Report")
report.append(f"Generated: {datetime.now()}")
report.append("")
# Quality Scores
report.append("## Quality Metrics")
for doc, score in self.quality_scores.items():
status = "ā
" if score >= 85 else "ā ļø" if score >= 70 else "ā"
report.append(f"{status} {doc}: {score}/100")
# Issues Summary
report.append("## Issues Found")
report.append(f"- Errors: {len(self.errors)}")
report.append(f"- Warnings: {len(self.warnings)}")
# Detailed Issues
for error in self.errors:
report.append(f"ā {error.file}:{error.line} - {error.message}")
return "\n".join(report)
```
---
ā
Validation Checklist
- [x] Comprehensive validation rules documented
- [x] SPEC compliance patterns included
- [x] TAG verification system explained
- [x] Quality metrics calculation patterns provided
- [x] Python script patterns included
- [x] CI/CD integration examples shown
- [x] English language confirmed
---
### Level 3: Advanced Patterns (Expert Reference)
> **Note**: Advanced patterns for complex scenarios.
**Coming soon**: Deep dive into expert-level usage.
---
## šÆ Best Practices Checklist
**Must-Have:**
- ā
[Critical practice 1]
- ā
[Critical practice 2]
**Recommended:**
- ā
[Recommended practice 1]
- ā
[Recommended practice 2]
**Security:**
- š [Security practice 1]
---
## š Context7 MCP Integration
**When to Use Context7 for This Skill:**
This skill benefits from Context7 when:
- Working with [docs]
- Need latest documentation
- Verifying technical details
**Example Usage:**
```python
# Fetch latest documentation
from moai_adk.integrations import Context7Helper
helper = Context7Helper()
docs = await helper.get_docs(
library_id="/org/library",
topic="docs",
tokens=5000
)
```
**Relevant Libraries:**
| Library | Context7 ID | Use Case |
|---------|-------------|----------|
| [Library 1] | `/org/lib1` | [When to use] |
---
## š Decision Tree
**When to use moai-docs-validation:**
```
Start
āā Need docs?
ā āā YES ā Use this skill
ā āā NO ā Consider alternatives
āā Complex scenario?
āā YES ā See Level 3
āā NO ā Start with Level 1
```
---
## š Integration with Other Skills
**Prerequisite Skills:**
- Skill("prerequisite-1") ā [Why needed]
**Complementary Skills:**
- Skill("complementary-1") ā [How they work together]
**Next Steps:**
- Skill("next-step-1") ā [When to use after this]
---
## š Official References
Metadata
```yaml
skill_id: moai-docs-validation
skill_name: Documentation Validation & Quality Assurance
version: 1.0.0
created_date: 2025-11-10
updated_date: 2025-11-10
language: english
word_count: 1400
triggers:
- keywords: [documentation validation, content verification, quality assurance, spec compliance, tag verification, documentation audit, quality metrics]
- contexts: [docs-validation, @docs:validate, quality-audit, spec-compliance]
agents:
- docs-auditor
- quality-gate
- spec-builder
freedom_level: high
context7_references:
- url: "https://en.wikipedia.org/wiki/Software_quality"
topic: "Software Quality Metrics"
- url: "https://github.com/moai-adk/moai-adk"
topic: "MoAI-ADK SPEC Standards"
```
---
## š Version History
** .0** (2025-11-12)
- ⨠Context7 MCP integration
- ⨠Progressive Disclosure structure
- ⨠10+ code examples
- ⨠Primary/secondary agents defined
- ⨠Best practices checklist
- ⨠Decision tree
- ⨠Official references
---
**Generated with**: MoAI-ADK Skill Factory
**Last Updated**: 2025-11-12
**Maintained by**: Primary Agent (doc-syncer)Quick Install
$
npx ai-builder add skill jg-chalk-io/moai-docs-validationDetails
- Type
- skill
- Author
- jg-chalk-io
- Slug
- jg-chalk-io/moai-docs-validation
- Created
- 6d ago