Audit Flow
Description
Claude Code skill for interactive system flow tracing across CODE, API, AUTH, DATA, NETWORK layers. SQLite persistence, Mermaid export, git merge driver.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
auditflow
Think before you build. Audit after you ship.
An [Agent Skill](https://agentskills.io) for thinking about systems before (and after) you build them.
Tell your AI agent to trace a flow — it walks through your codebase recording every step in SQLite, then exports Mermaid diagrams, Markdown reports, JSON, and YAML. Works with [Claude Code](https://docs.anthropic.com/en/docs/claude-code), [OpenAI Codex CLI](https://github.com/openai/codex), and any agent that supports the [Agent Skills spec](https://agentskills.io/specification).
Why
Most teams jump straight to code. The architecture lives in someone's head, a stale Confluence page, or a whiteboard photo rotting in Slack.
audit-flow makes system thinking a first-class artifact:
- Before building — sketch the flow as a DAG. Which layers? What triggers what? Where does data move? Your brainstorm session produces a queryable database and exportable diagrams, not ephemeral notes.
- After building — trace the real implementation. Compare what you planned vs what you built. The ideation flow and the documentation flow live in the same database.
- When things break — trace the bug path. Your incident post-mortem links back to the original design flow. Findings accumulate across sessions.
- Over time — 10 audits later, you have a queryable map of your entire system. New engineer joins?
audit.py listshows every flow ever traced.
It's TDD for architecture. Trace the flow f
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