Cohzen (cz)

Cohzen is a local-first toolkit that statically reconstructs, audits, and records LangGraph applications without runtime execution.

⚡ 30-Second Quickstart

# 1. Install Cohzen
pip install cohzen

# 2. Reconstruct your agent's architecture statically (zero execution)
cz scan .

# 3. Audit your observability and telemetry coverage
cz audit .

📸 What You Get

1. Terminal Architecture Flow & Scorecard (cz scan .)

Cohzen traverses your repository's AST, discovers LangGraph StateGraph workflows, links node handlers to LLM invocations and @tool bindings, and displays a crisp architecture report:

╭───────────────────── Cohzen Architecture Scanner (v0.1) ─────────────────────╮
│                                                                              │
│  Scanned Target: ./my-langgraph-agent                                        │
│  Frameworks:     ✓ langgraph                                                 │
│  Files Examined: 4 total (3 Python files)                                    │
│  Scan Duration:  0.60 ms                                                     │
│                                                                              │
│  Graphs Detected: 1  • Compiled: 1  • Registered Nodes: 2  • Edges/Routes: 3 │
│  Node Handlers:   1  • LLM Call Sites: 1  • Tools Defined: 2  • ToolNodes: 1  │
│                                                                              │
╰──────────────────────────────────────────────────────────────────────────────╯
╭───────── Graph #1: builder (StateGraph) StateSchema: MessagesState ──────────╮
│ ✔ COMPILED -> variable: app at agent_tools.py:43                             │
╰───────────────────────────── agent_tools.py:31 ──────────────────────────────╯
╭───── 🌐 Architecture Flow (Nodes • Edges • Tools • Checkpointer • LLMs) ─────╮
│                                                                              │
│     ● START                                                                  │
│       │                                                                      │
│       ▼                                                                      │
│       ├── ? route: 'tools' ──► tools                                         │
│       ├── ? route: 'finish' ──►  ● END                                       │
│    ╔══ 🛠️ tools (ToolNode) ═══════════════════════════════╗                  │
│    ║  Tools: search_docs, calculate_metrics                                  │
│    ╚══════════════════════════════════════════════════════╝                  │
│    ┌── 🤖 tools (tool_node) ──────────────────────┐                          │
│    │  🧠 LLM: None (logic/router)                                            │
│    └───────────────────────────────────────────────────────┘                 │
│       └──► assistant                                                         │
│                                                                              │
╰──────────────────────────────────────────────────────────────────────────────╯
                          Registered Nodes & Handlers                           
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
┃ Node Name    ┃ Handler / Location ┃ LLM Calls & Models ┃ Tools Bound / Att.  ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
│ 🤖 assistant │ assistant          │ langchain          │ bound: search_docs, │
│              │ (agent_tools.py:21)│ (model.invoke)     │ calculate_metrics   │
│ 🤖 tools     │ tool_node          │ Tool Execution     │ ToolNode(...)       │
│              │ (agent_tools.py:33)│                    │                     │
└──────────────┴────────────────────┴────────────────────┴─────────────────────┘

You can also export native Mermaid diagrams (cz scan . --mermaid) or launch the interactive browser visualizer (cz view .).

2. Automated Pull Request Architecture Gate

In CI/CD, Cohzen posts an automated scorecard directly on pull requests to prevent unmonitored agent drifts:

### 🛡️ Cohzen Agent Architecture & Telemetry Audit

| Status | Metric | Value |
|:---:|:---|:---|
| 🟢 | **Architecture Scan** | 1 graph · 4 nodes · 5 edges |
| 🟢 | **Telemetry Coverage** | 100% (4/4 nodes instrumented) |
| 🔍 | **Active Tracers** | LangSmith (`LANGCHAIN_TRACING_V2=true`) |
| ⚠️ | **Checkpointer** | MemorySaver (In-memory only — state lost on restart) |

<details>
<summary>🗺️ View Mermaid Architecture Flow</summary>

```mermaid
flowchart TD
  START([START]) --> assistant
  assistant -->|conditional| tools
  assistant -->|conditional| END([END])
  tools --> assistant

🚀 Installation

Install Cohzen via pip, uv, or pipx:

# Using pip
pip install cohzen

# Using uv
uv add cohzen

# As an isolated global CLI with pipx
pipx install cohzen

Note: Once installed, both cz and cohzen command aliases are available in your terminal.

🔍 CLI Commands

For detailed flags and subcommands, run cz --help or cz <command> --help.

🛡️ GitHub Action Usage

Enforce architecture hygiene and telemetry coverage in CI/CD by adding the official composite action to your repository's workflow (.github/workflows/agent-gate.yml):

name: Agent Architecture Gate

on:
  pull_request:
    branches: [main]

jobs:
  cohzen-gate:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write # Required if comment-pr is true
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - run: pip install cohzen

      - name: Cohzen Agent Architecture & Telemetry Gate
        uses: cohzenai/cohzen@v0.3.2
        with:
          path: "."
          min-coverage: "80"
          fail-on-missing-telemetry: "true"
          comment-pr: "true"

See the complete CI/CD Integration Guide for full action inputs, outputs, and multi-directory examples.

🧩 Support Matrix

Cohzen is continuously tested across the following matrix:

See docs/supported-frameworks.md for the complete list of supported LLM detectors (OpenAI, Anthropic, Google, Groq, Grok, LiteLLM) and observability providers (LangSmith, Langfuse, Arize Phoenix, Traceloop, AgentOps, W&B Weave).

🔒 Privacy & Data Handling

Cohzen is built on strict local-first principles:

1. Local CLI Execution: Cohzen's CLI does not send your code, prompts, or run data anywhere. Analysis and execution recording run purely on your local machine. External communication (such as GitHub Actions PR comments or future OTLP telemetry export) is strictly opt-in and under user control.
2. Local SQLite Storage: When local capture is enabled (cz init or cz capture), runtime records are stored in a local SQLite database (.cohzen/executions.db) that is automatically added to your .gitignore.
3. Pattern-Based, Best-Effort Secret Redaction: Before runtime payloads are committed to SQLite, Cohzen runs sensitive keys and text through a configurable redaction processor that masks common API keys, passwords, bearer tokens, and credential patterns (e.g. AWS, OpenAI, GitHub). Heuristic pattern matching is best-effort and cannot guarantee detection of custom token formats or proprietary secrets embedded in unstructured prompt text.
4. Configurable Retention: Control data volume via .cohzen/config.toml with strict caps on payload size (max_payload_bytes), run history (max_runs), and age (max_age_days).
5. Fail-Open Architecture: Runtime hooks fail open: if any capture error or database write occurs, your application execution continues unaffected without raising exceptions.

See SECURITY.md for our full security and vulnerability disclosure policy.

⚠️ Limitations & Honest Boundaries

To maintain trust and predictability, here is what Cohzen does not do:

• Static AST Limitations: cz scan inspects source code without importing or executing it. It cannot resolve dynamically constructed node names (e.g. graph.add_node(eval(var))), graphs assembled from remote network responses, or runtime metaprogramming.
• LangGraph Focus: Static scanning is currently optimized for LangGraph applications. Support for LlamaIndex Workflows, CrewAI, and AutoGen is in design and scheduled on our ROADMAP.md.
• Local Development Capture: The runtime capture engine is designed for local developer iteration, testing, and debugging. It is not intended as a multi-tenant, high-throughput production APM.
• Uninstalling the Hook: Always run cz deinit before running pip uninstall cohzen to cleanly unregister the environment's .pth startup hook.
• Execution Side Effects: Any execution under capture runs real user code with real side effects (making live LLM API calls and executing live tool handlers). Deterministic, mocked offline replay does not yet exist.
• Manifest Stability: cz scan --json emits the immutable CohzenManifest v0.1 specification. Manifest schemas are strictly versioned (see docs/manifest.md).

🧪 Testing

Cohzen maintains a rigorous test suite of unit tests, integration tests, runtime hooks, and real-world fixture projects:

# Run all 114 tests
pytest tests/ -v

# Run with test coverage (78% suite coverage)
pytest --cov=cz --cov-report=term-missing tests/

Includes 10 real-world architectural fixture projects under tests/fixtures/real_world/ verifying single-file graphs, multi-module graphs, tool binding, conditional routing, subgraphs, and dynamic fallbacks.

🤝 Contributing & Maintenance Expectations

Cohzen is maintained by a solo builder part-time.

• Response Times: Please expect replies to issues and pull request reviews within 48 to 72 hours.
• Contributing Guide: We warmly welcome external contributions! Please read CONTRIBUTING.md for local environment setup, testing steps, and PR guidelines.
• Adding Detectors: Want to add support for a new LLM provider, tool pattern, or observability vendor? Check out our step-by-step guide in docs/adding-a-detector.md.
• Developer Certificate of Origin (DCO): All commits must be signed off with git commit -s.
• Code of Conduct: This project adheres to the Contributor Covenant 2.1 (CODE_OF_CONDUCT.md).

📄 License

Cohzen is licensed under the Apache License, Version 2.0. See the LICENSE and NOTICE files for details.