Validate and refactor Markdown documentation against source code using heuristics + LLM
Project description
docval
AI Cost Tracking
This project uses AI-generated code. Total cost: $0.4500 with 3 AI commits.
Generated on 2026-04-14 using openrouter/qwen/qwen3-coder-next
Validate and refactor Markdown documentation against source code — detect outdated, orphaned, duplicate, and invalid docs using heuristics + optional LLM.
How it works
docs/ ──→ chunk by heading ──→ heuristic checks ──→ cross-ref with code ──→ (optional) LLM ──→ report/fix
Three validation layers, each progressively deeper:
- Heuristic validator (fast, free) — empty sections, broken internal links, TODO/FIXME markers, duplicate detection via
difflib, stale version references, archive path detection, explicit deprecation markers - Cross-reference validator (fast, free) — checks that backtick-quoted symbols (
ClassName,function_name), import paths in code blocks, and CLI commands actually exist in the project source - LLM validator (optional, paid) — semantic validation via
litellmfor chunks that heuristics couldn't resolve with high confidence
Installation
pip install docval
With LLM support:
pip install docval[llm]
From source:
git clone https://github.com/wronai/docval.git
cd docval
pip install -e ".[dev]"
CLI Usage
Scan and report issues
docval scan docs/
docval scan docs/ --project /path/to/repo -v
docval scan docs/ -o report.md
docval scan docs/ -o report.json
Fix documentation (dry-run by default)
docval fix docs/ # preview changes
docval fix docs/ --no-dry-run # apply fixes
docval fix docs/ --no-dry-run --llm # with LLM validation
Generate a patch file
docval patch docs/ -o fixes.txt
docval patch docs/ --llm --model gpt-4o -o fixes.txt
View documentation statistics
docval stats docs/
LLM validation
export OPENAI_API_KEY=sk-...
docval scan docs/ --llm --model gpt-4o-mini
docval scan docs/ --llm --model anthropic/claude-sonnet-4-20250514
docval scan docs/ --llm --model groq/llama-3.3-70b-versatile
Any model supported by litellm works.
Python API
from pathlib import Path
from docval.pipeline import scan
from docval.reporters import ConsoleReporter, MarkdownReporter
# Run validation
result = scan(
docs_dir=Path("docs/"),
project_root=Path("."),
use_llm=False,
)
# Print to console
ConsoleReporter(verbose=True).report(result)
# Write markdown report
MarkdownReporter().report(result, Path("validation-report.md"))
Using individual validators
from docval.chunker import chunk_directory
from docval.context import build_context
from docval.validators import HeuristicValidator, CrossRefValidator
# Chunk docs
doc_files = chunk_directory(Path("docs/"))
# Build project context
ctx = build_context(Path("."))
# Run heuristics
heuristic = HeuristicValidator(ctx=ctx)
heuristic.validate(doc_files)
# Cross-reference check
crossref = CrossRefValidator(ctx=ctx)
crossref.validate(doc_files)
# Inspect results
for f in doc_files:
for chunk in f.chunks:
if chunk.issues:
print(f"{f.relative_path}:{chunk.line_start} [{chunk.status.value}] {chunk.heading}")
for issue in chunk.issues:
print(f" {issue.severity.value}: {issue.message}")
What it detects
| Check | Layer | Example |
|---|---|---|
| Empty sections | Heuristic | Heading with no body text |
| Broken internal links | Heuristic | [guide](./deleted-file.md) |
| Deprecated markers | Heuristic | DEPRECATED, OBSOLETE, DO NOT USE |
| Archive path | Heuristic | Files in docs/archive/ directories |
| Stale versions | Heuristic | References to v1.x when project is v3.x |
| Duplicates | Heuristic | >80% similar content across files |
| TODO/FIXME | Heuristic | Unfinished documentation markers |
| Orphaned code refs | CrossRef | `NonExistentClass` in backticks |
| Broken imports | CrossRef | from mypackage.deleted import X in code blocks |
| Semantic accuracy | LLM | Content that doesn't match actual project behavior |
Architecture
src/docval/
├── cli.py # Click CLI: scan, fix, patch, stats
├── pipeline.py # Orchestrates: discover → chunk → validate → report
├── models.py # Data models: DocChunk, DocFile, ValidationResult
├── chunker.py # MD → heading-based semantic chunks
├── context.py # Build project context (AST, git, .toon files)
├── validators/
│ ├── heuristic.py # Rule-based checks (free, fast)
│ ├── crossref.py # Code ↔ docs cross-reference
│ └── llm_validator.py # Semantic validation via litellm
├── actions/
│ └── executor.py # Apply fixes: delete, archive, patch
└── reporters/
├── console.py # Rich CLI output
├── markdown_report.py # .md report
└── json_report.py # .json for CI/CD
Integration with .toon files
docval understands .toon.yaml files from the code2llm ecosystem. When present, it extracts module names, class names, and exported functions for cross-referencing, giving more accurate orphaned-reference detection.
License
Licensed under Apache-2.0.
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