🔍 docto-trace-storage

Deep storage auditing for Google Drive.
Part of the Docto Trace open-source suite.

What is this?

docto-trace-storage is a high-performance, open-source data auditing tool. It is the first module of the Docto Trace suite, designed to map and analyze "digital chaos" across cloud storage providers (starting with Google Drive). The goal is to provide deep visibility into storage structures, identifying digital dementia (orphaned files, zombies, and duplicates) to prepare organizations for AI-readiness and Centralized Memory — all safely from your own machine.

Read-Only, always. The tool never modifies or deletes files. It only observes and reports.

Your data stays local. The Drive API is called directly from your machine. No data passes through any Docto infrastructure.

Installation & Quick Start

The fastest way to get started is using the onboard command. It will guide you through creating a virtual environment, installing dependencies, setting up Google Cloud credentials, and running your first scan.

# 1. Clone the repository
git clone https://github.com/Docto-Studio/docto-trace-storage.git
cd docto-trace-storage

# 2. Run the onboarding wizard
pip install -e .
docto-trace onboard

The wizard will handle:

Environment check (offering to create a .venv/)
Dependency installation (including the optional Interactive UI)
Google Cloud setup (guiding you through creating your own credentials.json)
Authentication (logging into your Google Drive)
AI-Readiness (configuring an LLM provider like OpenAI or Anthropic)
Initial Scan (launching the dashboard immediately)

Features

Feature	Status
Google Drive OAuth2 authentication	✅ v0.1
Service Account support	✅ v0.1
Async recursive folder traversal	✅ v0.1
True cumulative folder sizes	✅ v0.1
Top-N largest folders (root excluded)	✅ v0.1
Deep folder detection	✅ v0.1
`report.json` export (strict Pydantic schema)	✅ v0.1
Rich terminal summary	✅ v0.1
🧟 Digital Dementia detection (stale > N months)	✅ v0.2
♻️ Content deduplication (MD5 + fallback)	✅ v0.2
Duplicate file path tracing	✅ v0.2
📊 Modern Streamlit Dashboard UI (`--ui`)	✅ v0.2
Actionable remediation `action_plan`	✅ v0.2
Bundled credentials (zero-setup for end users)	✅ v0.2
Bring Your Own Credentials (`setup` wizard)	✅ v0.2
`login` / `logout` auth lifecycle	✅ v0.2

Claude Skill (AI-native interface)

docto-trace-storage ships with a ready-to-use Claude Skill that lets you audit your Google Drive through natural language — no terminal required.

User → "Scan my Drive and find what's wasting space"
Claude → runs docto-trace scan → analyses report.json → responds with insights

The Skill actively invokes the CLI on your machine via a thin subprocess wrapper. It follows the exact same read-only guarantee as the CLI itself.

Install the Skill

# 1. Package the skill
cd skill/
zip -r docto-trace-storage.zip docto-trace-storage/

# 2. Upload to Claude → claude.ai/customize/skills

Enterprise admins can provision the Skill org-wide via Admin → Customize → Skills. See skill/README_SKILL.md for the full deployment guide.

Example prompts

Prompt	What happens
"Scan my Google Drive"	Full audit, default settings
"Find duplicate files in my Drive"	Scan + filter to duplicate groups
"Which files haven't been touched in 3 years?"	Scan with `--stale-threshold 36`
"Show me my 20 largest folders"	Scan with `--top 20`

The CLI (pip install docto-trace-storage) works fully standalone — the Skill is an additive layer that delegates 100% to it.

Trust & Privacy

Are you handing your private Drive to a stranger's app? No.

Read-only scopes only — the OAuth2 consent grants only drive.readonly and drive.metadata.readonly. The API physically cannot write, move, or delete anything.
100% local execution — your credentials, your token, and your Drive data never leave your machine. There is no Docto backend, no telemetry, no analytics.
Bring Your Own Credentials — you can create your own Google Cloud project and register your own OAuth2 app in ~5 minutes. Your token is then issued against your GCP project, which you control fully.

# Create your own GCP credentials (interactive wizard)
docto-trace setup

See Using Your Own Google Cloud Credentials for the full guide.

Installation

For end users (zero setup)

The package ships with Docto's OAuth2 credentials bundled inside. Install from PyPI and scan — the browser consent screen is the only step needed.

# Install from PyPI
pip install docto-trace-storage

# Scan immediately — no credentials.json needed
docto-trace scan

From source (contributors / developers)

git clone https://github.com/Docto-Studio/docto-trace-storage.git
cd docto-trace-storage

# Install editable with dev tools
pip install -e ".[dev]"

Build your own wheel

python -m build --wheel
# → dist/docto_trace_storage-0.2.1-py3-none-any.whl

Requirements: Python 3.10+

Quick Start

# Check version
docto-trace --version      # → docto-trace-storage v0.2.1

# Option A — Zero setup (uses bundled Docto credentials)
docto-trace scan            # browser opens for OAuth2 consent on first run

# Option B — Full control (your own GCP project)
docto-trace setup           # guided 4-step wizard
docto-trace login           # authenticate
docto-trace scan            # run audit
docto-trace logout          # clear session

CLI Reference

`docto-trace ui`

Launches a modern, sleek, interactive Streamlit dashboard to visualize the generated report.json. Features a beautiful Dark Theme, Top 10 folder grid, precise data storage metrics, and actionable item tables for addressing Digital Dementia.

docto-trace ui output/report.json

`docto-trace --version` / `-v`

docto-trace --version   # docto-trace-storage v0.2.1
docto-trace -v          # same

`docto-trace setup`

Interactive 4-step wizard to create your own Google Cloud project and OAuth2 credentials. Run this once if you want full control over the app registration.

docto-trace setup
docto-trace setup --output ~/my-creds.json

`docto-trace login`

Authenticate with Google Drive and cache the token locally. Subsequent commands reuse the cached token silently.

docto-trace login
docto-trace login --credentials ./my-credentials.json
docto-trace login --service-account ./sa-key.json   # skip browser flow

`docto-trace logout`

Delete the cached token. The next scan or login will trigger a fresh browser flow.

docto-trace logout
docto-trace logout --revoke     # also revoke on Google's servers

`docto-trace scan`

The core command. Traverses Google Drive, runs all audits, and produces report.json.

# Full scan with defaults
docto-trace scan

# Scan and automatically launch the interactive UI dashboard
docto-trace scan --ui

# Narrow to a specific folder by Drive ID
docto-trace scan --root-id 1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgVE2upms

# Cap depth, show top 20, custom output dir
docto-trace scan --max-depth 5 --top 20 --output ./reports/

# Zombie threshold: flag files not modified in 12 months (default: 24)
docto-trace scan --stale-threshold 12

# Use your own credentials file
docto-trace scan --credentials ./my-credentials.json

# Use a service account (no browser flow)
docto-trace scan --service-account ./sa-key.json

Flag	Default	Description
`--root-id` / `-r`	`root`	Drive folder ID to start from
`--max-depth` / `-d`	unlimited	Max folder depth to traverse
`--top` / `-n`	`10`	Top-N largest folders to show
`--deep-threshold`	`5`	Depth to flag as "deep"
`--stale-threshold` / `-S`	`24`	Months without modification = zombie
`--credentials` / `-c`	`credentials.json`	OAuth2 credentials file
`--output` / `-o`	`output/`	Directory for `report.json`
`--ui` / `--no-ui`	`--no-ui`	Auto-launch Streamlit dashboard
`--service-account` / `-s`	(none)	Service account key path

Terminal Output Example

🔐 Authenticating with Google Drive…
ℹ️  Using Docto bundled credentials. Run docto-trace setup to use your own.
🌐 Opening browser for Google Drive authorization…  ← first run only

🔍 Scanning: My Drive
⠙ Traversing folders… [00:18]

─────────────── 📦 Storage Overview ───────────────
  Root:          My Drive
  Total files:   14,832
  Total folders: 1,204
  Total size:    48.3 GB
  Max depth:     9

─────────────── 🏆 Top 10 Largest Folders ───────────────
 Rank  Folder     Path              Files    Size
 1     Projects   My Drive/Projects 8,241    31.2 GB
 2     Archive    My Drive/Archive  3,102    10.5 GB

─────────────── 🧟 Zombie Files (381 stale) ───────────────
 File             Path                             Last Modified  Size
 old_invoice.pdf  My Drive/Finance/old_invoice.pdf  2020-01-15    2.1 MB

─────────────── ♻️  Duplicate Groups (70 groups · 104 MB wasted) ───────────────
 Fingerprint       Path                                  Size/copy  Wasted
 c8cd4fe0ab7a7fe8… My Drive/Backup/8CDA554B…mov          12.0 MB    12.0 MB
 (2 copies)        My Drive/Photos/8CDA554B…mov

──────────────── ✅ Report saved ────────────────
  Output: output/report.json

Report Schema (v0.2.1)

The output report.json follows the HealthReport Pydantic schema:

{
  "schema_version": "0.2.1",
  "generated_at": "2026-03-23T10:00:00Z",
  "storage_tree": { "root_name": "My Drive", "total_files": 14832, "total_size_bytes": 51876044800 },
  "insights": {
    "top_folders": [...],
    "deep_folders": [...]
  },
  "zombies": [
    { "file_id": "...", "name": "old_invoice.pdf", "path": "My Drive/Finance/old_invoice.pdf",
      "last_modified": "2020-01-15T10:30:00Z", "size_bytes": 2202009, "reason": "stale" }
  ],
  "duplicates": [
    { "fingerprint": "c8cd4fe0…", "files": ["id1", "id2"],
      "file_names": ["invoice_final.pdf", "invoice_copy.pdf"],
      "file_paths": ["My Drive/Docs/invoice_final.pdf", "My Drive/Backup/invoice_copy.pdf"],
      "size_bytes_per_copy": 2097152, "wasted_bytes": 2097152 }
  ],
  "action_plan": [
    { "severity": "warning",  "category": "zombie",    "description": "..." },
    { "severity": "critical", "category": "duplicate", "description": "..." }
  ]
}

Deduplication strategy:

Primary key — md5Checksum from the Drive API (binary files: PDFs, images, Office docs)
Fallback key — "<size_bytes>:<normalized_name>" for Google-native files (Docs, Sheets, Slides)

Using Your Own Google Cloud Credentials

If you want full control over the OAuth2 app registration — so your consent screen, quotas, and audit logs belong entirely to you — run the setup wizard:

docto-trace setup

It walks you through 4 steps, opening each Google Cloud Console page in your browser:

Create a GCP project — gives you ownership of the app
Enable the Google Drive API — only the two read-only scopes
Configure the OAuth2 consent screen — add yourself as a test user
Download credentials.json — the wizard validates it locally

Then authenticate with your own credentials:

docto-trace login --credentials ./credentials.json
docto-trace scan  --credentials ./credentials.json

You can revoke access at any time from Google Cloud Console → Credentials, independently of the Docto project.

Configuration

All settings can be overridden with environment variables prefixed DOCTO_TRACE_, or in a .env file:

Variable	Default	Description
`DOCTO_TRACE_CREDENTIALS_PATH`	`credentials.json`	OAuth2 credentials file
`DOCTO_TRACE_TOKEN_PATH`	`token.json`	Cached token path
`DOCTO_TRACE_SERVICE_ACCOUNT_PATH`	(none)	Service account key path
`DOCTO_TRACE_MAX_DEPTH`	(unlimited)	Max folder nesting to traverse
`DOCTO_TRACE_DEEP_FOLDER_THRESHOLD`	`5`	Depth to flag as "deep"
`DOCTO_TRACE_TOP_N`	`10`	Top-N largest folders
`DOCTO_TRACE_STALE_THRESHOLD_MONTHS`	`24`	Zombie detection cutoff (months)
`DOCTO_TRACE_OUTPUT_DIR`	`output/`	Report output directory
`DOCTO_TRACE_PAGE_SIZE`	`1000`	Drive API items per page

Development

make install    # Install with dev dependencies
make lint       # Lint with ruff
make fix        # Auto-fix lint issues
make test       # Run unit tests (no credentials needed)
make typecheck  # Run mypy

Tests run entirely offline — no Google credentials required:

python -m pytest tests/ -v
# 48 passed in 0.18s

Architecture

docto_trace/
├── cli.py                  # Typer root entry point
├── config.py               # Pydantic settings (env-var overridable)
├── data/
│   └── credentials.json    # Bundled Docto OAuth2 credentials (package resource)
├── auth/
│   ├── google_drive.py     # OAuth2 + service account flow (bundled fallback)
│   └── token_store.py      # Token serialization
├── connectors/
│   ├── base.py             # AbstractConnector interface
│   └── google_drive.py     # Drive API (async, paginated, thread-safe)
├── engine/
│   ├── traversal.py        # Iterative BFS tree builder (bounded concurrency)
│   ├── analytics.py        # Phase 1: top-N, deep-folder analytics
│   └── auditor.py          # Phase 2: zombie detection + deduplication
├── schemas/
│   ├── storage.py          # FileNode, FolderNode, StorageTree
│   └── report.py           # HealthReport, ZombieFile, DuplicateGroup, …
└── commands/
    ├── setup.py            # `docto-trace setup`  — BYOC wizard
    ├── login.py            # `docto-trace login`  — OAuth2 flow
    ├── logout.py           # `docto-trace logout` — clear token
    ├── scan.py             # `docto-trace scan`   — core audit command
    └── report.py           # `docto-trace report` — extended report (v0.3)

Key design decisions:

Bundled credentials — docto_trace/data/credentials.json is shipped inside the wheel via importlib.resources, enabling zero-setup for end users. Technical users override with --credentials or docto-trace setup.
Schema-first — all data models defined in Pydantic before any logic is written; report.json is machine-readable by other Docto modules.
Pure audit functions — analytics.py and auditor.py are pure functions with no I/O; trivially unit-testable without credentials.
Iterative BFS traversal — avoids Python stack overflows on large Drives; bounded to MAX_CONCURRENT=20 parallel API calls via asyncio.Semaphore.
Thread-safe HTTP — each thread-pool worker gets its own httplib2.Http via threading.local, preventing socket corruption.

Roadmap

Version	Focus
v0.1	Structural mapping — folder sizes, deep nesting
v0.2	Data hygiene — digital dementia detection, deduplication, Streamlit UI dashboard, auth lifecycle
v0.3	Extended reporting — owner analysis, sharing audit, cost estimation
v0.4	AI readiness score — structured/unstructured ratio, naming entropy

Name		Name	Last commit message	Last commit date
Latest commit History 27 Commits
.github/workflows		.github/workflows
docto_trace		docto_trace
skill		skill
tests		tests
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
pyproject.toml		pyproject.toml

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🔍 docto-trace-storage

What is this?

Installation & Quick Start

Features

Claude Skill (AI-native interface)

Install the Skill

Example prompts

Trust & Privacy

Installation

For end users (zero setup)

From source (contributors / developers)

Build your own wheel

Quick Start

CLI Reference

docto-trace ui

docto-trace --version / -v

docto-trace setup

docto-trace login

docto-trace logout

docto-trace scan

Terminal Output Example

Report Schema (v0.2.1)

Using Your Own Google Cloud Credentials

Configuration

Development

Architecture

Roadmap

License

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`docto-trace ui`

`docto-trace --version` / `-v`

`docto-trace setup`

`docto-trace login`

`docto-trace logout`

`docto-trace scan`

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