Automate evidence-based architecture documentation directly from GitHub repos.
This AI agent retrieves a GitHub repository's metadata and file tree, analyzes key files, and extracts concrete architectural elements. It uses Claude Sonnet 4.5 with strict evidence rules to generate an architecture blueprint in Markdown with Mermaid diagrams and risk analysis. It pushes README_ARCH.md to the repository and optionally notifies a Slack channel.
Automates end-to-end blueprint generation from code evidence.
Fetch repo metadata, file tree, and key files from the GitHub repository.
Analyze evidence with Claude Sonnet 4.5 to extract architectures grounded in code.
Generate a Mermaid.js architecture diagram and a tech-stack analysis based on actual files.
Assemble a Markdown blueprint with diagrams, risk analysis, and evidence traceability.
Push README_ARCH.md to the repository’s default branch.
Notify stakeholders via Slack (if a token is provided) and surface a success confirmation.
This agent targets concrete repo workflow gaps: ensuring architecture docs derive directly from code evidence and are versioned with the repo. It replaces manual, error-prone documentation with automated, verifiable blueprints.
A simple 3-step system anyone can follow.
User submits the repository URL via a web form or webhook to start the flow.
Agent fetches repo metadata, file tree, and contents of key files (package.json, requirements.txt, Dockerfiles, entry points, etc.).
Claude Sonnet 4.5 analyzes evidence and generates README_ARCH.md with diagrams and risk analysis, then pushes to the default branch and notifies via Slack if configured.
A realistic scenario showing task, time, and outcome.
Scenario: A public repository named 'example/project' is submitted. Within roughly 8–12 minutes, the AI Agent analyzes code evidence, generates a complete README_ARCH.md with Mermaid diagrams and a risk analysis, pushes it to the default branch, and sends a Slack notification if configured.
Specifically aligned roles and reasons.
Auto-generates up-to-date architecture docs that reflect actual code evidence.
Provides quick onboarding docs grounded in real dependencies and files.
Offers a single source of truth for system architecture and risk.
Speeds up vendor codebase assessments with evidence-backed diagrams.
Adds polished, evidence-based documentation to showcase repos.
Streamlines creation and maintenance of architecture docs directly in repos.
Key tools the agent operates inside.
Fetches repo metadata, file tree, and key files; pushes README_ARCH.md to default branch.
Analyzes evidence and generates architecture content with strict, evidence-based reasoning.
Sends a notification to configured channels when the blueprint is published.
Common scenarios where the agent shines.
Answers to common questions about the AI agent.
An evidence-based architecture blueprint is a formal Markdown document generated from real code evidence found in the repository. It includes architecture diagrams (Mermaid), a tech-stack analysis drawn from actual dependency files, and a risk assessment tied to specific files or patterns. The content is produced by Claude Sonnet 4.5 with a strict prompt that prevents claiming technologies not present in the codebase. The result is a verifiable, versioned document that reflects the repository’s true architecture.
The agent is designed to work with public repositories by default, using published metadata and files. For private repos, credentials with the appropriate scopes are required, and access is governed by the host environment’s security controls. The blueprint generation still relies on evidence; any technology claimed must be traceable to actual files. If private access is not configured, the agent will return an actionable error indicating missing permissions.
The agent relies on evidence from the codebase. If Docker or Terraform files are absent, those technologies will not be described in the blueprint. The result will emphasize the technologies and architecture observable in the repository, ensuring the output remains accurate and grounded. This prevents hallucinations and ensures stakeholders see only what the code supports.
Yes, when configured, the agent pushes the generated README_ARCH.md to the repository’s default branch. This creates a versioned artifact that aligns with the repository history. If automatic pushing is disabled, you can review and approve changes before merging. Notifications are sent post-push to confirm completion.
The agent attempts to locate a defined set of evidence sources (package.json, requirements.txt, Dockerfiles, entry points, etc.). If none are found, the blueprint will reflect available evidence and flag missing sources. It will still generate a coherent architecture narrative based on what exists, with explicit notes about the gaps. You can then add or adjust files to strengthen future blueprints.
Slack notification is optional and depends on whether a token is provided and configured. When enabled, stakeholders receive real-time updates on blueprint publication. If disabled, the agent still pushes the blueprint and logs the activity for auditing. Notifications can be tailored to channels or individuals as needed.
Credentials are scoped to the minimum required permissions and managed through your token vault or secret manager. Access is limited to the repository in question, and activities are logged for traceability. The workflow is designed to avoid exposing secrets in outputs and to prevent leakage through AI-generated content. Always follow your organization’s security guidelines for token management.
Automate evidence-based architecture documentation directly from GitHub repos.
