A powerful CLI & Python library for context that feeds your prompts

Command-line tool and Python API for intelligent code aggregation and analysis.
Surface relevant files. Build optimal context. Track velocity.
Examine code quality metrics. Evaluate and improve your codebase.
All processing stays local - your code never leaves your machine.

Quick StartCLI DocsAPI DocsSee Examples

See It In Action

Context Building
$ tenets distill "add mistral api to summarizer"
Output
Context building - Analyzing files
Analyzing and ranking relevant files
Context building - Building context
Building optimized context with summaries
Ranking Files
$ tenets rank "fix summarizing truncation bug" --tree
Output
Ranking the most relevant files
Ranking files by relevance using multi-factor scoring
Code Analysis
$ tenets examine . --complexity --hotspots --ownership
Output
Code analysis
Comprehensive code analysis with metrics
Quality Metrics
$ tenets examine . --show-details --hotspots --format html
Output
Quality metrics
Code quality metrics and improvement suggestions
Sessions
$ tenets session create payment-integration
$ tenets tenet add "Always validate user input" --priority critical --category security
$ tenets tenet add "Use type hints in Python" --priority high --category style
$ tenets instill --session payment-integration
$ tenets system-instruction set "Prefer small, safe diffs and add tests" --enable
$ tenets distill "add OAuth2 refresh tokens" --session payment-integration --remove-comments --condense
Output
Sessions - Creating session
Creating a session and adding tenets
Sessions - Managing tenets
Managing and instilling guiding principles
Sessions - Building context
Building context with session-aware tenets
Velocity
$ tenets momentum --team --since "last month" --detailed
Output
Velocity
Team velocity metrics and trends
Visualization
$ tenets viz deps --format html --output interactive.html
Output
Visualization
D3.js interactive dependency graph visualization

Core Features

Intelligent Context Building

Multi-factor ranking algorithm that goes beyond keyword matching. Analyzes code structure, import relationships, Git history, and semantic meaning to surface exactly the files you need for any development task.

  • Multi-Factor Ranking: Keywords, structure, imports, path relevance, and Git signals
  • Optional ML: Semantic embeddings and transformers when tenets[ml] is installed
  • Summarization: Rules-based and ML summarizers built-in; LLMs only if API keys enabled
  • Token Optimization: Budget-aware packing and model-specific token counting
  • Lightweight Extras: Extras-based dependency architecture keeps core lean

Code Quality Metrics & Evaluation

Comprehensive evaluation system that assesses code quality, identifies hotspots, tracks technical debt, and provides actionable insights. Use tenets not just for prompting but for continuous code quality monitoring and improvement.

  • Complexity Analysis: Cyclomatic, cognitive, and Halstead metrics
  • Quality Evaluation: Maintainability index and code health scoring
  • Technical Debt Tracking: Identify and prioritize refactoring needs
  • Test Coverage Analysis: Find untested code paths and improve reliability
  • Code Pattern Detection: Identify anti-patterns and best practices

Stateful Prompting & Tenets

Build complex features iteratively with persistent sessions. Define guiding principles (tenets) that shape how AI understands your codebase. Perfect for ongoing conversations with AI assistants and maintaining context across multiple prompts.

  • Persistent Context: Maintain state across multiple CLI invocations
  • Guiding Tenets: Define principles that guide AI interactions
  • Incremental Building: Add context without starting over each time
  • Session Branching: Explore alternatives without losing work
  • SQLite Storage: Reliable local session persistence and history

Development Intelligence & Insights

Track velocity, identify bottlenecks, and understand team patterns. Visualize your architecture, monitor code evolution, and make data-driven decisions about refactoring, technical debt, and resource allocation.

  • Velocity Tracking: Monitor team and individual productivity metrics
  • Hotspot Analysis: Find frequently changing and problematic areas
  • Dependency Visualization: Understand architecture and coupling
  • Contributor Analytics: Track code ownership and expertise
  • Trend Analysis: Monitor quality and velocity changes over time

How Tenets Works

1

Input

Natural language prompt
or specific query

→
2

Scan

Parallel file discovery
respecting .gitignore

→
3

Analyze

Language analyzers & AST
structure and metrics

→
4

Rank

Multi-factor scoring
keywords, structure, git

→
5

ML (Optional)

Embeddings & semantic
similarity when enabled

→
6

Summarize & Output

Token budgeting & summaries
LLMs optional via API keys

Installation Options

Quick InstallQuick

pip install tenets

Core features - lightweight, no ML dependencies

Full FeaturesAll

pip install tenets[all]

Everything including ML models and visualization

Light NLPLight

pip install tenets[light]

Keyword extraction, TextRank, metrics without deep learning

MLML

pip install tenets[ml]

Transformers, embeddings, vector search, providers

VisualizationViz

pip install tenets[viz]

Graphs, plots, and visual dashboards

Web InterfaceWeb

pip install tenets[web]

FastAPI, Uvicorn, SSE, uploads

Install & Build from SourceSource

git clone https://github.com/jddunn/tenets.git cd tenets && pip install -e .

Latest development version with all updates

Docker (Install & Build)Docker

# Official Docker commands are coming soon

Official Docker image and compose examples coming soon

View Installation Guide View on GitHub