DocGuard

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The enforcement layer for Spec-Driven Development. Validate. Score. Enforce. Ship documentation that AI agents can actually use.

CI npm npm downloads PyPI License: MIT Node.js Runtime deps Spec Kit Extension Glama MCP Registry

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✨ See what DocGuard catches in 30 seconds — no install, no setup:

npx docguard-cli demo

Runs against a baked-in sample project with intentional drift and shows you the findings + a clear path to fixing them.

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Table of Contents

• What is DocGuard?
• Why DocGuard?
• Quick Start
• Spec Kit Integration
• Usage
• Validators
• Templates
• AI Agent Support
• Slash Commands
• Examples
• Testing
• Enterprise Adoption
• CI/CD Integration
• What's New
• File Structure
• Configuration
• Research Credits

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What is DocGuard?

DocGuard enforces Canonical-Driven Development (CDD) — a methodology where documentation is the source of truth, not an afterthought. AI writes the docs, DocGuard validates them.

Traditional Development	Canonical-Driven Development
Code first, docs maybe	Docs first, code conforms
Docs rot silently	Drift is tracked and enforced
Docs are optional	Docs are required and validated
One AI agent, one context	Any agent, shared context via canonical docs

DocGuard is an official GitHub Spec Kit community extension. It validates the artifacts that Spec Kit creates, ensuring your specs stay high-quality throughout the development lifecycle.

📖 Philosophy · 📋 CDD Standard · ⚖️ Comparisons · 🔬 Validation · 🗺️ Roadmap

Architecture

graph TD
    CLI["CLI Entry<br/>docguard.mjs"] --> Commands["Commands (20)"]
    Commands --> guard["guard"]
    Commands --> generate["generate"]
    Commands --> score["score"]
    Commands --> diagnose["diagnose"]
    Commands --> setup["setup wizard"]
    Commands --> other["diff · init · fix · trace · impact · sync<br/>explain · memory · upgrade · agents · hooks · badge · ci · watch"]

    guard --> Validators["Validators (27)"]
    generate --> Scanners["Scanners (4)<br/>routes · schemas · doc-tools · speckit"]
    score --> Scoring["Weighted Scoring<br/>8 categories"]
    diagnose --> Validators
    diagnose --> AIPrompts["AI-Ready<br/>Fix Prompts"]

    Validators --> Output["Output"]
    Scanners --> Output
    Scoring --> Output
    Output --> Terminal["Terminal"]
    Output --> JSON["JSON"]
    Output --> Badge["Badge"]

    style CLI fill:#2d5016,color:#fff
    style Validators fill:#1a3a5c,color:#fff
    style Scanners fill:#1a3a5c,color:#fff
    style Output fill:#5c3a1a,color:#fff

Distribution: Node.js core (npm) · Python wrapper (PyPI) · GitHub Action (action.yml) · Spec Kit Extension (ZIP)

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Why DocGuard?

Documentation that drifts from code is worse than no documentation — it confidently misleads humans and AI agents alike. DocGuard treats your canonical docs as an enforced contract: deterministic validators diff what the docs claim against what the code does, on every commit, with no LLM required. The full thesis (and the research behind it) lives in PHILOSOPHY.md; recent feature highlights moved below.

The field data backs the enforcement-over-instructions bet: an ETH Zurich study across 138 repos / 5,694 agent PRs found the most popular style of agent-instruction file hurts agent performance, and practitioners keep converging on the same lesson — written rules are routinely ignored; programmatic checks are what agents (and humans) actually respect. That is exactly the layer DocGuard provides: not another instructions file, but the validator suite that makes the instructions and docs verifiably true.

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⚡ Quick Start

Package naming: this repo is raccioly/docguard; the published package is docguard-cli on both npm and PyPI; the installed command is docguard. Same project — the -cli suffix is just the registry name. The package runs no install scripts, so npm i -g docguard-cli --ignore-scripts is equivalent.

Node.js (npm)

# No install needed — run directly
npx docguard-cli diagnose

# Or install globally
npm i -g docguard-cli
docguard diagnose

Python (PyPI)

pip install docguard-cli
docguard diagnose

Note: The Python package is a thin wrapper that delegates to npx. Node.js 18+ is required on the system.

More ways to integrate

• pre-commit — changed-only guard on every commit:

  repos:
    - repo: https://github.com/raccioly/docguard
      rev: v0.29.0
      hooks: [{ id: docguard-guard }]   # docguard-guard-full for pre-push
  

• MCP (Claude, Cursor, any MCP client) — claude mcp add docguard -- npx -y docguard-cli mcp; 5 read-only tools (guard, score, explain, verify-claims, diagnose). Registry manifest ships in-repo (server.json, Smithery-ready).
• GitLab CI — component staged at templates/ci/gitlab-component.yml (guard/score/ci job with a SARIF artifact).
• Homebrew — brew install raccioly/tap/docguard (formula in packaging/homebrew/).

Core Workflow

# 1. Initialize docs for your project
npx docguard-cli init

# 2. Or reverse-engineer docs from existing code
npx docguard-cli generate

# 3. AI diagnoses issues and generates fix prompts
npx docguard-cli diagnose

# 4. Validate — use as CI gate
npx docguard-cli guard

# 5. Check maturity score
npx docguard-cli score

The AI Loop

diagnose  →  AI reads prompts  →  AI fixes docs  →  guard verifies
   ↑                                                       ↓
   └───────────────── issues found? ←──────────────────────┘

diagnose is the primary command. It runs all validators, maps every failure to an AI-actionable fix prompt, and outputs a remediation plan. Your AI agent runs it, fixes the docs, and runs guard to verify.

Mechanical vs. agent fixes

DocGuard splits drift into two kinds and is explicit about which is which:

Kind	Example	How it's fixed
Mechanical (deterministic)	An endpoint documented in API-REFERENCE.md that the OpenAPI spec confirms is gone	docguard fix --write deletes the row + detail block itself — no AI
Agent (needs judgment)	Rewriting an X-Ray prose section as CloudWatch; writing a new endpoint's request/response	Routed to an AI agent via diagnose / fix --doc prompts

docguard fix --write only touches docs marked <!-- docguard:generated true --> (override with --force), is idempotent, and prints exactly what changed. It never rewrites prose — that stays with the agent.

Hands-off loop (set and forget)

guard ──▶ fix --write (mechanical, auto) ──▶ guard ──▶ diagnose (agent prompts for the rest)

• CI / pre-commit: docguard hooks --type pre-commit --auto-fix installs a hook that applies mechanical fixes, re-stages the docs, then runs guard; anything left is surfaced as agent prompts.
• Agent-driven: docguard diagnose --auto scaffolds missing docs and applies mechanical fixes, then emits prompts for the content rewrites that remain.
• JSON for automation: guard/diagnose --format json include a mechanicalFixes array and tag each issue mechanical vs agent, so an agent can apply or delegate precisely.

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🌱 Spec Kit Integration

DocGuard is a community extension for GitHub's Spec Kit framework. While Spec Kit focuses on creating specifications (via AI slash commands like /speckit.specify and /speckit.plan), DocGuard focuses on validating their quality.

How They Work Together

┌─────────────────┐          ┌──────────────────┐
│    Spec Kit      │          │    DocGuard       │
│                  │          │                   │
│  /speckit.specify│ ──────→  │  docguard guard   │
│  Creates specs   │          │  Validates specs  │
│  (AI-driven)     │          │  (automated)      │
└─────────────────┘          └──────────────────┘

Phase	Tool	What happens
1. Initialize	specify init	Creates .specify/ directory and templates
2. Write specs	/speckit.specify	AI creates spec.md with FR-IDs, user stories
3. Validate	docguard guard	Checks spec quality (mandatory sections, FR/SC IDs)
4. Plan	/speckit.plan	AI creates plan.md with technical context
5. Validate	docguard guard	Checks plan quality (sections, structure)
6. Tasks	/speckit.tasks	AI creates tasks.md with phased breakdown
7. Validate	docguard guard	Checks task quality (phases, T-IDs)
8. Implement	/speckit.implement	AI writes code
9. Enforce	docguard guard	Final quality gate — CI/CD

What DocGuard Validates in Spec Kit Projects

• spec.md — Mandatory sections (User Scenarios, Requirements, Success Criteria), FR-xxx IDs, SC-xxx IDs
• plan.md — Summary, Technical Context, Project Structure sections
• tasks.md — Phased task breakdown (Phase 1, 2, 3+), T-xxx task IDs
• constitution.md — Detected at .specify/memory/constitution.md or project root
• Requirement traceability — FR, SC, NFR, US, AC, UC, SYS, ARCH, MOD, T IDs

Installing as a Spec Kit Extension

specify extension add docguard

This installs DocGuard's slash commands (/docguard.init, /docguard.guard, /docguard.review, /docguard.fix, /docguard.update) into your AI agent's command palette.

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Usage

DocGuard ships 20 commands (the "Daily 5" + 15 situational tools, including the zero-install demo, the mcp server, and the ci pipeline gate). Six additional one-shot scaffolders are accessed via docguard init --with <name>. Seven v0.19 commands continue to work as deprecation aliases through v0.20.x — see MIGRATION-v0.20.md.

The Daily 5 — what you'll reach for 95% of the time:

Command	What It Does
init	Bootstrap a project (--wizard for interactive · --with <name> for scaffolders)
guard	Validate against canonical docs — 27 validators
diff	Show gaps between docs and code (--since <ref> for impact mode)
sync	Refresh code-truth doc sections — keeps memory always up to date
score	CDD maturity score (0-100; --diff for delta between refs)

Tools (situational, but day-to-day useful):

Command	Purpose
demo	Zero-install showcase — runs guard against a baked-in drifting fixture (npx docguard-cli demo)
diagnose	AI orchestrator — guard → emit fix prompts in one command
fix	Generate AI fix instructions for specific docs (--doc <name> --format prompt)
fix --write	Apply deterministic fixes (no AI — version bumps, counts, anchors, sections)
fix --history	Audit log of every mechanical fix applied (from .docguard/fixed.json)
generate	Reverse-engineer docs from existing codebase (--plan for AI scan) — includes auto-generated Mermaid ER diagrams from your detected schemas (Prisma/Drizzle/TypeORM/Sequelize/Django/Rails) in DATA-MODEL.md
agent	One-shot agent task graph — ordered, pre-filled code-truth, per-task verify (--format json)
explain <warning|CODE>	Paste any warning — or a finding code like SEC001 — to get the validator's docstring, fix path, and how to suppress
verify --semantic	Extract documented numbers/limits/enums (retention days, rate limits, GSI/role counts, status enums) as a task list for an agent to check against code — the semantic-drift class regex/AST can't see
verify --instructions	Audit AGENTS.md/CLAUDE.md themselves for drift: duplicate rules, never-vs-always contradictions, stale file pointers, unknown commands — plus clustered rule pairs as agent judgment tasks
feedback	Report likely false positives back to DocGuard — local-first record + a 1-click prefilled, redacted GitHub issue (zero typing)
mcp	MCP server — exposes guard/score/explain/verify/report/diagnose as native tools for Claude, Cursor, and any MCP client. Stdio: claude mcp add docguard -- npx docguard-cli mcp. Team-shared HTTP: docguard mcp --transport http --port 8585 (loopback by default; non-loopback binds require --api-key)
report	Compliance-evidence bundle for audits — guard verdict + CDD score + ALCOA+ attributes + fix history, stamped with git commit and a tamper-evident sha256 integrity hash (--format json, --out <file>). Evidence, not a gate: always exits 0
ci	Pipeline gate: guard + score in one command — never scaffolds or touches source; its only write is its own .docguard/history.jsonl (opt out: --no-history). --threshold <n> fails below a score, --fail-on-warning for strict mode, --format json for parsers
score --trend	Score trajectory from recorded ci runs — sparkline, delta, and the last 10 runs with commit stamps
memory	Per-domain accuracy headline (endpoints / entities / env / tech)
memory --diff	Drill into which specific claims don't match code
memory --pack	Write .docguard/context-pack.md — compact, code-truth-stamped session-start context for AI agents
score --diff	Drill into which checks pulled each category down
trace / trace --reverse <file>	Requirements traceability — forward AND reverse
trace --features	Per-feature spec-adherence scores (requirement coverage, task completion, task evidence, artifacts) — worst-first with fix hints
upgrade [--apply] [--pr]	Check + migrate .docguard.json schema; --pr opens a PR
watch	Live mode: re-run guard on file changes

init --with <name> scaffolders — picked at init time:

Scaffolder	What It Generates
agents	AGENTS.md, CLAUDE.md, .cursor/rules/, .github/copilot-instructions.md
hooks	Git pre-commit / pre-push hooks
ci	GitHub Actions / pipeline YAML
badge	Shields.io score badges for README
llms	llms.txt (AI-friendly summary)
publish	External doc-site config (Mintlify) — experimental

Run them solo (docguard init --with hooks) or stacked (docguard init --with agents,hooks,badge,ci).

Deprecation aliases — setup · agents · hooks · ci · badge · llms · publish · impact keep working in v0.20.x with a yellow stderr warning. audit → guard is permanent (no warning). See MIGRATION-v0.20.md.

CLI Flags

Flag	Description	Commands
--dir <path>	Project directory (default: .)	All
--verbose	Show detailed output	All
--quiet / -q	Suppress banner — for hooks, CI loops, scripts	All
--format json	Machine-readable output (clean JSON, no ANSI bleed)	guard, score, diff, trace, diagnose, memory, impact, explain
--format sarif	SARIF 2.1.0 output — findings as rules/results for GitHub Code Scanning and SARIF dashboards	guard
--format junit	JUnit XML output — one testcase per validator, for GitLab CI (artifacts:reports:junit), Jenkins, Azure DevOps, CircleCI	guard
--update-baseline	Adopt DocGuard on a legacy repo without a red day one: freeze today's findings into a committed .docguard.baseline.json; guard/ci then gate only NEW drift. Suppression is always visible ("N pre-existing finding(s) suppressed"), and --no-baseline shows the full picture	guard
--full	Generate llms-full.txt (full doc bodies inlined) instead of the llms.txt link index	llms
--pack	Write .docguard/context-pack.md — agent session-start context	memory
--sync	Regenerate the agent-file family (CLAUDE.md, Copilot, Cursor, …) from AGENTS.md; hash-marked, never touches hand-written files without --force	agents
--check	CI gate for the synced agent-file family — exit 2 when a variant is stale	agents
--force	Overwrite existing files (creates .bak backups)	generate, agents, init
--force-redo	Bypass ping-pong suppression in .docguard/fixed.json	fix --write
--profile <name>	Starter / standard / enterprise	init
--no-spec-kit	Skip auto-init of .specify/ / .agent/ scaffolding	init
--changed-only [--since <ref>]	Pre-commit lite mode (5 fast validators on changed files only)	guard
--timings	Per-validator wall-time profile (slowest first)	guard
--show-failing	Show warnings/errors even when status is PASS	guard
--pin	Record running CLI version into .docguard.json (reproducibility)	guard
--diff	Per-category drill-down	score, memory
--check-only	Exit 1 if behind (for CI)	upgrade
--apply	Actually run the migration	upgrade
--pr	Open a PR with the migration	upgrade
--reverse <file>	Reverse traceability (code → docs)	trace
--no-indirect	Skip the reverse-import-graph analysis (docs about modules that import a changed file)	impact, diff --since
--prs	Open-PR doc-conflict analysis — two PRs impacting the same canonical doc = merge-order risk (needs the gh CLI)	impact
--transport http --port --host --api-key --path	Serve MCP over Streamable HTTP instead of stdio (team-shared server; loopback-only unless an api-key is set)	mcp
--history	Show fix audit log	fix

Example Output

$ npx docguard-cli generate

🔮 DocGuard Generate — my-project
   Scanning codebase to generate canonical documentation...

  Detected Stack:
    language: TypeScript ^5.0
    framework: Next.js ^14.0
    database: PostgreSQL
    orm: Drizzle 0.33
    testing: Vitest
    hosting: AWS Amplify

  ✅ ARCHITECTURE.md (4 components, 6 tech)
  ✅ DATA-MODEL.md (12 entities detected)
  ✅ ENVIRONMENT.md (18 env vars detected)
  ✅ TEST-SPEC.md (45 tests, 8/10 services mapped)
  ✅ SECURITY.md (auth: NextAuth.js)
  ✅ REQUIREMENTS.md (spec-kit aligned)
  ✅ AGENTS.md
  ✅ CHANGELOG.md
  ✅ DRIFT-LOG.md

  Generated: 9  Skipped: 0

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🔍 Validators

DocGuard runs 27 automated validators on every guard check. Every one is language-aware as of v0.16 — patterns for Python (test_*.py), Rust (tests/*.rs), Go (*_test.go), Java (*Test.java), Ruby (*_spec.rb), PHP, and JS/TS all match.

#	Validator	What It Checks	Default
1	Structure	Required CDD files exist	✅ On
2	Doc Sections	Canonical docs have required sections (or N/A markers)	✅ On
3	Docs-Sync	Routes/services referenced in docs + OpenAPI cross-check	✅ On
4	Drift-Comments	// DRIFT: comments logged in DRIFT-LOG.md (skips test files by default)	✅ On
5	Changelog	CHANGELOG.md has [Unreleased] section	✅ On
6	Test-Spec	Tests exist per TEST-SPEC.md rules	✅ On
7	Environment	Env vars documented, .env.example exists	✅ On
8	Security	No hardcoded secrets in source code	✅ On
9	Architecture	Imports follow layer boundaries (honors config.ignore)	✅ On
10	Freshness	Docs not stale relative to code changes (rename-aware via git log --follow)	✅ On
11	Traceability	Requirement IDs (FR, SC, NFR, US, AC, T) trace to tests	✅ On
12	Docs-Diff	Code artifacts match documented entities	✅ On
13	API-Surface	API-REFERENCE.md endpoints match real routes (OpenAPI cross-check)	✅ On
14	Metadata-Sync	Version refs consistent across docs	✅ On
15	Docs-Coverage	Code features referenced in documentation	✅ On
16	Doc-Quality	Writing quality (readability, passive voice, atomicity, IEEE 830)	✅ On
17	TODO-Tracking	Untracked TODOs/FIXMEs and skipped tests (skips test files by default)	✅ On
18	Schema-Sync	Database models documented in DATA-MODEL.md	✅ On
19	Spec-Kit	Spec quality validation (FR-IDs, mandatory sections, phased tasks)	✅ On
20	Cross-Reference	Internal markdown links + anchors resolve (with "did you mean?" hints); Obsidian wikilinks validated when the repo uses them as file links (.obsidian present or a target resolves)	✅ On
21	Generated-Staleness	source=code sections match scanner output; status: draft doc age	✅ On
22	Canonical-Sync	DocGuard's own README count claims match code-truth (DocGuard repo only — N/A elsewhere)	✅ On
23	Metrics-Consistency	Hardcoded numbers match actual counts	✅ On
24	Surface-Sync	Item-level enumerable drift — names in doc tables/lists (commands, checks, etc.) match code-truth (opt-in via surfaceSync.surfaces; N/A unless configured)	✅ On
25	Diff-Suspicion	Change-driven: a doc/agent-instruction file that references code changed since the ref AND shares removed domain symbols is flagged for review (arXiv 2010.01625, F1 74.7)	✅ On
26	Reference-Existence	Two-revision check: a backticked code symbol present when the doc was last updated but gone at HEAD is flagged as outdated (arXiv 2212.01479)	✅ On
27	API-Doc-Smells	Bloated (≥300 words) / Lazy (≤6 prose words) API documentation units, keyed on signature-headed sections (F1 0.90/0.95)	✅ On

Per-validator controls (in .docguard.json):

{
  "validators": {
    "test-spec": false,                 // disable (kebab-case OR camelCase both accepted)
    "freshness": true
  },
  "severity": {
    "todoTracking": "high",             // warnings fail CI
    "freshness": "low"                  // warnings ignored for exit code
  }
}

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📄 Templates

DocGuard ships 18 professional templates with metadata, badges, and revision history:

Template	Type	Purpose
ARCHITECTURE.md	Canonical	System design, components, layer boundaries
DATA-MODEL.md	Canonical	Schemas, entities, relationships
SECURITY.md	Canonical	Auth, permissions, secrets management
TEST-SPEC.md	Canonical	Test strategy, coverage requirements
ENVIRONMENT.md	Canonical	Environment variables, deployment config
REQUIREMENTS.md	Canonical	Spec-kit aligned FR/SC IDs, user stories
DEPLOYMENT.md	Canonical	Infrastructure, CI/CD, DNS
ADR.md	Canonical	Architecture Decision Records
ROADMAP.md	Canonical	Project phases, feature tracking
KNOWN-GOTCHAS.md	Implementation	Symptom → gotcha → fix entries
TROUBLESHOOTING.md	Implementation	Error diagnosis guides
RUNBOOKS.md	Implementation	Operational procedures
VENDOR-BUGS.md	Implementation	Third-party issue tracker
CURRENT-STATE.md	Implementation	Deployment status, tech debt
AGENTS.md	Agent	AI agent behavior rules
CHANGELOG.md	Tracking	Change log
DRIFT-LOG.md	Tracking	Deviation tracking
llms.txt	Generated	AI-friendly project summary (llmstxt.org)

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🤖 AI Agent Support

DocGuard works with every major AI coding agent. All canonical docs are plain markdown — no vendor lock-in.

Agent	Compatibility	Auto-Generate Config
Google Antigravity	✅	docguard agents --agent antigravity
Claude Code	✅	docguard agents --agent claude
GitHub Copilot	✅	docguard agents --agent copilot
Cursor	✅	docguard agents --agent cursor
Windsurf	✅	docguard agents --agent windsurf
Cline	✅	docguard agents --agent cline
Google Gemini CLI	✅	docguard agents --agent gemini
Kiro (AWS)	✅	—

Always-on nudge hook (Claude Code)

docguard hooks --claude            # install   (remove: docguard hooks --claude --remove)

Registers a PostToolUse hook in the project's .claude/settings.json. After the agent edits a canonical doc it is nudged to run docguard guard --changed-only; after it edits a code file the docs reference, it is nudged toward docguard impact. Merge-safe (only DocGuard's own entry is ever added/removed), throttled to one nudge per file per 30 minutes, and the hook runtime can never break a session (errors are silent by contract). Explicit opt-in — init never installs it for you.

---

⚡ Slash Commands

DocGuard provides AI agent slash commands for integrated workflows. Installed automatically via docguard init or specify extension add docguard:

Command	What It Does
/docguard.init	Initialize Canonical-Driven Development in a new or existing project
/docguard.guard	Run quality validation — check all 27 validators
/docguard.review	Analyze doc quality and suggest improvements
/docguard.fix	Generate targeted fix prompts for specific issues
/docguard.update	Update canonical docs after code changes — detect drift and sync documentation

These commands are installed into your AI agent's command directory:

.github/commands/     → GitHub Copilot
.cursor/rules/        → Cursor
.gemini/commands/     → Google Gemini
.claude/commands/     → Claude Code
.agents/workflows/    → Antigravity

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🧠 AI Skills (Enterprise)

Beyond slash commands, DocGuard provides 4 enterprise-grade AI skills — deep behavior protocols that tell AI agents not just what to run, but how to think, validate, and iterate. Skills are modeled after Spec Kit's skill architecture.

Skill	Lines	What It Does
docguard-guard	155	6-step quality gate with severity triage (CRITICAL→LOW), structured reporting, remediation
docguard-fix	195	7-step research workflow with per-document codebase research and 3-iteration validation loops
docguard-review	170	Read-only semantic cross-document analysis with 6 analysis passes and quality scoring
docguard-score	165	CDD maturity assessment with ROI-based improvement roadmap and grade progression

Workflow Hooks

DocGuard integrates into the spec-kit workflow as an automated quality gate:

Hook	When	Behavior
after_implement	After /speckit.implement	Mandatory — always runs DocGuard guard
before_tasks	Before /speckit.tasks	Optional — reviews doc consistency
after_tasks	After /speckit.tasks	Optional — shows CDD maturity score

Orchestration Scripts

For advanced users and CI/CD pipelines, DocGuard includes bash scripts with --json output:

Script	Purpose
docguard-check-docs.sh	Discover project docs, return JSON inventory with metadata
docguard-suggest-fix.sh	Run guard, parse results, output prioritized fixes
docguard-init-doc.sh	Initialize canonical doc with metadata header

---

📁 Examples

Three real-world projects to see DocGuard in action:

Example	Scenario	What You'll See
01-express-api	Node.js API with zero docs	Cold-start: generate → instant coverage
02-python-flask	Python app with drifted docs	Drift detection: catch when docs lie
03-spec-kit-project	Full CDD + Spec Kit	Gold standard: what maturity looks like

See examples/README.md for step-by-step instructions.

---

🧪 Testing

Test Suite

npm test    # 33 tests across 18 describe blocks

Covers all 15 CLI commands, project type detection, compliance profiles, JSON output format, and help completeness.

CI Matrix

Node.js	OS	Status
18	ubuntu-latest	✅
20	ubuntu-latest	✅
22	ubuntu-latest	✅

Self-Validation (Dogfooding)

DocGuard runs its own guard, score, diff, diagnose, and badge commands against itself in CI — ensuring the tool passes its own checks.

---

🏢 Enterprise Adoption

Everything runs local or in your CI — no SaaS, no data leaving your infra. The pieces that matter at company scale:

Need	DocGuard answer
Adopt on a legacy repo without a red pipeline on day one	guard --update-baseline freezes existing findings into a committed .docguard.baseline.json; only NEW drift gates from then on (suppression always visible)
Audit trail for compliance reviews	docguard report — commit-stamped evidence bundle (guard verdict, findings by code, CDD score, ALCOA+ data-integrity attributes, fix history) with a tamper-evident sha256 integrity hash
Every CI system, not just GitHub	guard --format sarif (GitHub Code Scanning) · --format junit (GitLab, Jenkins, Azure DevOps, CircleCI) · --format json (anything else)
Trajectory, not snapshots	docguard ci records every run to .docguard/history.jsonl; score --trend shows the sparkline + delta
AI agents on the team	MCP server (stdio or team-shared HTTP) exposes guard/score/explain/verify/report/diagnose as read-only tools; agents --sync keeps the whole agent-file family drift-proof
Data-integrity framing auditors know	ALCOA+ scoring (FDA 21 CFR Part 11 / EMA Annex 11 vocabulary) built into score and report

⚙️ CI/CD Integration

Full recipes: see docs-canonical/CI-RECIPES.md for guard, auto-fix (commits mechanical fixes back to PRs), nightly sync, score-on-PR, and pre-commit configs.

GitHub Actions — Guard (most common)

name: DocGuard Guard
on: [pull_request, push]
permissions: { pull-requests: write }   # for the sticky PR comment (optional)
jobs:
  docguard:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with: { fetch-depth: 0 }
      - uses: raccioly/[email protected]
        with:
          command: guard

On pull requests, guard mode also gives inline PR feedback (both default on):

Input	Default	Description
annotations	true	Inline ::error/::warning annotations on the PR diff, one per guard finding (capped at 50; a final notice reports how many were elided)
pr-comment	true	Sticky PR comment with the guard verdict, top findings (by code), and which canonical docs the PR's changed files impact (diff --since origin/<base>). Needs permissions: pull-requests: write; degrades to a log warning without it

Both run even when guard fails — that's when the feedback matters. Prefer native code-scanning integration? docguard guard --format sarif uploads straight to GitHub Code Scanning via github/codeql-action/upload-sarif.

GitHub Actions — Auto-Fix (commits mechanical fixes back)

name: DocGuard Auto-Fix
on: { pull_request: { types: [opened, synchronize, reopened] } }
permissions: { contents: write, pull-requests: write }
jobs:
  autofix:
    runs-on: ubuntu-latest
    if: github.event.pull_request.head.repo.full_name == github.repository
    steps:
      - uses: actions/checkout@v4
        with:
          ref: ${{ github.event.pull_request.head.ref }}
          token: ${{ secrets.GITHUB_TOKEN }}
          fetch-depth: 0
      - uses: raccioly/[email protected]
        with: { command: fix, auto-commit: 'true', comment-on-pr: 'true' }

Pre-commit Hook

npx docguard-cli hooks --type pre-commit

Workflow starters (copy directly)

Two ready-to-use templates ship with the Spec Kit extension and as standalone files:

• extensions/spec-kit-docguard/templates/github-workflows/docguard-guard.yml — mandatory CI gate
• extensions/spec-kit-docguard/templates/github-workflows/docguard-autofix.yml — PR auto-fix

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✨ What's New

Highlights of the current line (v0.29 → v0.33):

• Adoption baseline — guard --update-baseline freezes a legacy repo's existing findings into a committed .docguard.baseline.json; guard/ci then gate only NEW drift, with suppression always visible. Adopt today, burn down at your own pace.
• docguard report — commit-stamped compliance-evidence bundle (guard verdict, findings by code, CDD score, ALCOA+ attributes, fix history) with a tamper-evident sha256 integrity hash. Also exposed as the docguard_report MCP tool.
• Score history + score --trend — docguard ci records every run to .docguard/history.jsonl; the trend view shows the sparkline and delta over time.
• Three machine formats for guard — --format json, --format sarif (GitHub Code Scanning), and --format junit (GitLab, Jenkins, Azure DevOps, CircleCI).
• MCP server, stdio + team HTTP — guard/score/explain/verify/report/diagnose as read-only agent tools: claude mcp add docguard -- npx docguard-cli mcp.
• Agent-file family sync — agents --sync treats AGENTS.md as canonical and regenerates CLAUDE.md / .cursor/rules / Copilot / Gemini variants with drift-proof source-hash markers.
• verify --semantic and verify --instructions — extract documented numbers/limits/enums as agent verification tasks; audit the agent-instruction files themselves for contradictions and stale pointers.
• docguard agent — one-shot ordered task graph with pre-filled code-truth, collapsing ~10 agent round-trips into one call.

See CHANGELOG.md for the full history.

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📁 File Structure

your-project/
├── .specify/                        # Spec Kit (if using specify init)
│   ├── specs/
│   │   └── 001-feature/
│   │       ├── spec.md              # Requirements (FR-IDs, user stories)
│   │       ├── plan.md              # Implementation plan
│   │       └── tasks.md             # Task breakdown
│   ├── memory/
│   │   └── constitution.md          # Project principles
│   └── templates/
│
├── docs-canonical/                  # CDD canonical docs (the "blueprint")
│   ├── ARCHITECTURE.md              # System design, components
│   ├── DATA-MODEL.md                # Database schemas
│   ├── SECURITY.md                  # Auth, permissions, secrets
│   ├── TEST-SPEC.md                 # Required tests, coverage
│   ├── ENVIRONMENT.md               # Environment variables
│   └── REQUIREMENTS.md              # Spec-kit aligned FR/SC IDs
│
├── docs-implementation/             # Current state (optional)
│   ├── KNOWN-GOTCHAS.md
│   ├── TROUBLESHOOTING.md
│   ├── RUNBOOKS.md
│   └── CURRENT-STATE.md
│
├── AGENTS.md                        # AI agent behavior rules
├── CHANGELOG.md                     # Change tracking
├── DRIFT-LOG.md                     # Documented deviations
├── llms.txt                         # AI-friendly summary
└── .docguard.json                   # DocGuard configuration

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⚙️ Configuration

Create .docguard.json in your project root (auto-generated by docguard init):

{
  "projectName": "my-project",
  "version": "0.4",
  "profile": "standard",
  "projectType": "webapp",
  "validators": {
    "structure": true,
    "docsSync": true,
    "drift": true,
    "changelog": true,
    "testSpec": true,
    "security": true,
    "environment": true,
    "docQuality": true,
    "specKit": true
  }
}

See Configuration Guide for all options.

---

🔬 Research Credits

DocGuard's quality evaluation and documentation generation patterns are informed by peer-reviewed research from the University of Arizona and the Joint Interoperability Test Command (JITC), U.S. Department of Defense:

• AITPG — AI-driven Test Plan Generator using Multi-Agent Debate and RAG (Lopez et al., IEEE TSE 2026)
• TRACE — Telecom Root Cause Analysis through Calibrated Explainability (Lopez et al., IEEE TMLCN 2026)

Lead researcher: Martin Manuel Lopez · ORCID 0009-0002-7652-2385

See CONTRIBUTING.md for full citations.

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⭐ Star History

Star History Chart

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📄 License

MIT — Free to use, modify, and distribute.

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Made with ❤️ by Ricardo Accioly