docpistemic 0.2.0

Epistemic documentation coverage assessment - know what your docs know

📚 Docpistemic

Know what your docs know — and what they don't

0.2.0 (2026-05-07): Coverage assessment now counts every public class AND every module-level function discovered (previously capped at top-20 classes — most public functions were invisible). New --strict flag requires AST docstring presence (no substring-match fallback). See CHANGELOG.md.

What is Docpistemic?

Docpistemic applies epistemic principles to documentation assessment. Instead of just checking "does this function have a docstring?", it asks the harder question:

"Does the user know this feature exists?"

It measures the gap between what your code does and what your docs explain.

Installation

PyPI (Recommended)

pip install docpistemic

Docker

# Pull from DockerHub
docker pull nubaeon/docpistemic:latest

# Assess any GitHub repo
docker run --rm nubaeon/docpistemic assess https://github.com/user/repo

# Assess local project
docker run --rm -v $(pwd):/project nubaeon/docpistemic assess /project

Homebrew (macOS/Linux)

brew tap nubaeon/tap
brew install docpistemic

From Source

pip install git+https://github.com/Nubaeon/docpistemic.git

Quick Start

# Assess current project
docpistemic assess .

# Assess a GitHub repo
docpistemic assess https://github.com/user/repo

# JSON output for CI / compliance pipelines
docpistemic assess . --output json

# Strict mode — requires AST docstring presence, no substring-match fallback
docpistemic assess . --strict

# Show more undocumented items in the report
docpistemic assess . --depth 3 --verbose

# Log findings to Empirica (if you have an active session)
docpistemic assess . --log

--depth controls the report, not the denominator

--depth N controls how many undocumented items are surfaced in the report per category. The coverage denominator always counts every public class and every public module-level function the discoverer found — adding new functions to your project always moves the metric.

Depth	Mode	Undocumented preview	Use Case
1	Quick	top 20 per category	Fast CI checks
2	Standard	top 50 per category	Regular assessment
3	Thorough	top 100 per category	Pre-release audit

--strict: AST docstring as the primary signal

By default, an item is "documented" if its name appears anywhere in README.md or docs/*.md OR if it has an AST docstring. Substring match has false positives (a class named Commit matches every changelog entry). --strict mode requires an AST docstring — more honest, more conservative coverage %.

docpistemic assess .            # Permissive: substring or docstring
docpistemic assess . --strict   # Strict: docstring only

Example Output

============================================================
📚 DOCPISTEMIC ASSESSMENT
============================================================

🌔 Overall Coverage: 94.6%
   Features: 1745/1844 documented

📊 Epistemic Assessment:
   know: 0.95
   uncertainty: 0.05
   → Documentation is comprehensive

📋 Category Coverage:
--------------------------------------------------
   🌕 CLI Commands: 99.6% (272/273)
   🌕 Classes: 93.8% (380/405)
   🌔 Public Functions: 93.7% (991/1058)
   🌕 API Endpoints: 92.3% (72/78)
   🌕 Configuration: 100% (30/30)

💡 Recommendations:
   • Document Public Functions: _resolve_artifact_by_id, _walk_graph, ...
   • Document Classes: _ReadOnlyDB, ...

Discovered: 273 CLI commands, 405 classes, 1058 public functions,
            78 API endpoints, 30 config options (strict)
============================================================

How It Works

1. Discovery - Auto-detects CLI framework (argparse, click, typer), classes, public module-level functions, API routes (FastAPI / Flask / Django), config options
2. Documentation Scan - Reads README, docs/, docstrings
3. Coverage Mapping - Maps features → documentation (every class + function, no top-N cap)
4. Epistemic Assessment - Calculates know/uncertainty vectors
5. Recommendations - Prioritizes what to document next

Features

• 🔍 Auto-discovery - No config needed, works on any Python project
• 📊 Epistemic vectors - know/uncertainty scoring (powered by Empirica)
• 🌙 Moon phases - Visual coverage indicators
• 🎯 Actionable recommendations - Prioritized list of what to document
• 🔧 CI-ready - JSON output, exit codes for quality gates
• 🌐 Remote repos - Assess any public GitHub repo

Supported Frameworks

Category	Frameworks
CLI	argparse, click, typer, fire
Web	FastAPI, Flask, Django
Docs	README.md, docs/, docstrings

Philosophy

Why "Turtle Depth"?

The phrase "turtles all the way down" comes from a famous anecdote about infinite regress:

A scientist finishes a lecture on cosmology. An elderly woman in the audience objects: "What you have told us is rubbish. The world is really a flat plate supported on the back of a giant tortoise."

The scientist asks, "And what is the tortoise standing on?"

The woman replies: "You're very clever, young man, but it's turtles all the way down!"

The story illustrates a fundamental problem: any explanation requires a further explanation. In documentation, this manifests as a recursive question:

• Does feature X have docs? → Do the docs explain the context needed to understand X? → Do those docs explain their prerequisites? → ...

Traditional tools stop at the first turtle. Docpistemic goes deeper.

Epistemic vs Binary Coverage

Approach	Question	Answer
Traditional	"Is there a docstring?"	Yes/No
Docpistemic	"Would a user discover this feature?"	know/uncertainty vectors

This shifts focus from code coverage to user coverage — from what the code says to what the user knows.

Powered by Empirica

Docpistemic uses Empirica for epistemic assessment — the same framework used by AI agents for genuine self-awareness.

Why Empirica?

Empirica provides:

• Epistemic vectors (know/uncertainty) - calibrated self-assessment
• Moon phase indicators - visual coverage signals
• Finding logging - track documentation gaps over time
• Session continuity - maintain assessment history across sessions

Empirica Integration

When you install docpistemic, Empirica is installed as a dependency. You can optionally:

# Initialize Empirica in your project
empirica project-init

# Create a session
empirica session-create --ai-id your-name

# Run docpistemic with logging to track findings
docpistemic assess . --log

# View your documentation debt over time
empirica finding-log --list

This lets you track documentation coverage improvements across releases.

License

MIT License