Qiuner/birdview

Stop letting AI code blind. Map the architecture before every change with Birdview.

What it solves

Birdview addresses the "black box" problem of AI coding agents, where developers often only see the final code diff without understanding the AI's reasoning or the architectural impact of its changes. It prevents scope mistakes by forcing the agent to map the project and declare which modules and files will be affected before implementation begins.

How it works

Birdview acts as a skill for AI agents. The process happens in two stages:

  1. Mapping: The agent analyzes the source code to create an architecture.json file describing modules, their responsibilities, and how they connect.
  2. Execution: During a task, the agent records its planned scope and progress in an activity.jsonl file.

These files are then validated and rendered into a standalone, interactive HTML page. This page allows developers to visualize the system map, the specific files the agent intends to touch, the source evidence supporting those claims, and the verification checks the agent performed.

Who it’s for

It is designed for developers using AI coding agents (such as Claude Code, Codex, or DeepSeek Harness) who want more transparency and architectural control over the changes the AI introduces to their codebase.

Highlights

  • Visual Architecture Mapping: Transforms project structure into an interactive map of modules and relationships.
  • $’$Architecture-as-Code’$ Approach: Uses JSON schemas to ensure the agent's understanding of the system is structured and consistent.
  • Pre-implementation Validation: Allows users to catch scope errors before the AI finishes editing the code.
  • Zero-Infrastructure Viewer: Generates a standalone HTML file that opens in any browser without needing a deployed server.

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