> ## Documentation Index
> Fetch the complete documentation index at: https://docs.flintai.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Scan quickstart

> Prove your agents are production ready in less than 10 minutes

AI-powered analysis finds misconfigurations, risky tool access, missing guardrails, and other issues. Automatically triages false positives so you see real problems, not noise.

<Note>
  **Requirements:** Python 3.13 or later

  **Supported frameworks:** Google ADK, Google GenAI, Anthropic, OpenAI, OpenAI Agents SDK, LangGraph, CrewAI, AutoGen, HuggingFace Transformers, HuggingFace smolagents
</Note>

<Steps>
  <Step title="Install `flintai-cli`">
    Using a virtual environment is recommended to avoid dependency conflicts:

    ```bash theme={null}
    python3.13 -m venv .venv
    source .venv/bin/activate
    ```

    Install Flint AI CLI:

    ```bash theme={null}
    pip install flintai-cli
    ```
  </Step>

  <Step title="Configure your LLM provider">
    `flintai-cli` uses AI to read your agent code contextually and filter false positives. Run the interactive setup and select your LLM:

    ```bash theme={null}
    flintai init
    ```

    You'll be prompted to select a provider (Gemini, OpenAI, Anthropic, or LiteLLM), choose a model, and enter your API key. Your configuration is saved to `~/.flintai/.env`.

    <Accordion title="Where to get API keys">
      * **Google Gemini**: [aistudio.google.com/apikey](https://aistudio.google.com/apikey) (free tier available)
      * **OpenAI**: [platform.openai.com/api-keys](https://platform.openai.com/api-keys)
      * **Anthropic**: [console.anthropic.com/settings/keys](https://console.anthropic.com/settings/keys)
      * **LiteLLM**: Supports 100+ providers via proxy. See [docs.litellm.ai](https://docs.litellm.ai/docs/)
    </Accordion>

    <Tip>
      **Start free.** Google Gemini offers a free tier with generous limits — test `flintai-cli` with no API costs.
    </Tip>
  </Step>

  <Step title="Scan your Python agent code">
    Run the scan:

    ```bash theme={null}
    flintai scan .
    ```

    **Example output:**

    ```json theme={null}
    {
      "agents_found": 3,
      "framework_detected": "crewai",
      "findings": [
        {
          "category": "asi05_unexpected_code_execution",
          "ai_spm_severity": "Critical",
          "title": "Arbitrary Code Execution via eval()",
          "cvss_scores": { "base_score": 9.3 }
        }
      ]
    }
    ```

    `flintai scan` discovers agents in your codebase — you may find agents you didn't know existed. Results are saved to `scan_<timestamp>.json`.
  </Step>
</Steps>

<Tip>
  **Integrate with CI/CD.** Save `scan_<timestamp>.json` as a build artifact to prove validation before deployment. [Learn how →](#)
</Tip>

## Next steps

<CardGroup cols={2}>
  <Card title="Issues found?" icon="wrench" href="/flintai/cli/scan/scan-results">
    Understand severity scores and what needs fixing before deployment
  </Card>

  <Card title="Clean scan?" icon="flask" href="/flintai/cli/eval/getting-started">
    Get a 0.0-1.0 reliability score for agent runtime behavior
  </Card>
</CardGroup>