DEV Community: Cyber Audio Mind

I built code health agents that run on your dependency graph — no database, just Markdown

Cyber Audio Mind — Tue, 24 Feb 2026 10:55:08 +0000

The Problem

Every AI coding tool — Claude Code, Cursor, Copilot — needs to understand your codebase. But they don't. Not really.

They see individual files, but miss the big picture: which components depend on what, how API routes connect to database models, what auth pattern each page uses.

Current solutions like GitNexus solve this with a graph database (KuzuDB) and an MCP server. That's powerful, but it's also heavy: you need to run a server, install dependencies, and it only works with Claude Code.

I wanted something simpler — and I wanted to go further than just mapping code.

The Solution: Structured Markdown + Code Health Agents

Fondamenta ArchCode runs static analysis on your codebase and generates structured Markdown files. But in v0.3.0, it also runs rule-based agents on the project graph to find real issues.

npx fondamenta-archcode analyze    # Map everything
npx fondamenta-archcode agents     # Find issues

No database. No server. No runtime dependencies. Just .md files and actionable findings.

What It Generates

.planning/
├── DEPENDENCY-MAP.md          # Architecture overview, impact areas
├── AGENTS-REPORT.md           # Code health findings (with --report)
└── dependencies/
    ├── pages-atomic.md        # Every page: imports, auth, data fetching
    ├── components-atomic.md   # Every component: props, state, hooks, used-by
    ├── api-routes-atomic.md   # Every API route: methods, auth, models
    ├── lib-atomic.md          # Every utility: exports, imports, env vars
    ├── schema-crossref-atomic.md  # DB models, fields, relations, enums
    └── component-graph.md     # Visual dependency tree

Example: pages-atomic.md

### `/dashboard`

- **File:** `app/(dashboard)/dashboard/page.tsx`
- **Type:** Server Component
- **Auth:** auth()
- **Data Fetching:**
  - DB: findMany (courses)
  - DB: count (flashcards)
- **Components:** CourseCard, StatsWidget, RecentActivity

Every AI agent understands this format instantly. No special tools needed.

Code Health Agents (NEW in v0.3.0)

This is the real game-changer. After analyze builds the project graph, agents runs rule-based checks on it:

$ fondamenta agents --free

  ✓ dead-code .............. 3 findings (1 error, 2 warnings)
  ✓ circular-deps .......... 0 findings
  ✓ architecture-guard ..... 5 findings (2 warnings, 3 info)
  ○ security-scanner ....... skipped (PRO)

  ERROR  [dead-code] Orphan component
  │ File: components/legacy/OldWidget.tsx
  │ Component `OldWidget` is never imported or rendered
  │ → Remove the file or restore the import

  8 findings: 1 error, 4 warnings, 3 info | 3 agents ran | 9ms

3 Free Agents

Agent	What it checks
`dead-code`	Orphan components, unused exports, unreferenced lib files
`circular-deps`	Circular import chains using DFS 3-color cycle detection
`architecture-guard`	Files >500 lines, god components (>15 deps), mutation routes without auth

5 PRO Agents (license-gated)

Agent	What it checks
`security-scanner`	Auth gaps + DB access, env vars leaked to client bundles, insecure patterns
`schema-drift`	Models in code but not in schema, schema models never referenced
`performance-sentinel`	Heavy pages (>20 imports), unnecessary client components, API waterfalls
`convention-enforcer`	File naming, barrel exports, inconsistent auth patterns
`impact-analyzer`	Fan-in/fan-out hotspots, hub components, bridge files

CI Integration

fondamenta agents --ci    # Exit code 1 if errors found
fondamenta agents --report  # Generate AGENTS-REPORT.md

The business model is Open Core: free agents work for everyone, PRO agents require a license key. No server calls — validation is offline.

How It Works

Discovers files using fast-glob (respects .gitignore)
Parses TypeScript/TSX using the TypeScript Compiler API (not regex!)
Builds an in-memory graph of imports, exports, components, hooks
Classifies each file: page, component, API route, lib, hook
Analyzes Prisma schema for models, fields, and relations
Generates structured Markdown with consistent formatting
Runs agents on the graph — each agent is a pure function: (graph, config) → findings[]

The TypeScript Compiler API is key — it gives us a real AST. The agents are simple: they iterate over nodes and edges in the graph. No AI, no LLM calls. Pure rule-based analysis that runs in milliseconds.

Real-World Results

Tested on a 1000+ file Next.js project:

Metric	Value
Files analyzed	1,011
Pages mapped	116
Components mapped	487
API routes documented	291
DB models cross-referenced	109
Analysis time	3.4 seconds
Agents execution	9 milliseconds
Findings	601 (40 errors, 550 warnings, 11 info)

Full Command Set

fondamenta analyze             # Full codebase analysis
fondamenta agents              # Run code health agents
fondamenta agents --free       # Free agents only
fondamenta agents --agent dead-code  # Single agent
fondamenta agents --ci         # Exit 1 if errors (CI)
fondamenta agents --report     # Generate markdown report
fondamenta agents --list       # Show all agents
fondamenta diff                # Changes since last analysis
fondamenta diff --ci           # Exit 1 if outdated
fondamenta watch               # Auto-regenerate on changes
fondamenta ai-context --all    # CLAUDE.md + .cursorrules + copilot

vs Alternatives

	Fondamenta ArchCode	GitNexus	Repomix
Output	Structured .md files	Graph DB (KuzuDB)	Single concatenated file
Code health agents	8 agents (free + PRO)	No	No
Runtime deps	None	KuzuDB + MCP server	None
AI integration	Any tool (reads files)	Claude Code only (MCP)	Any tool
Framework-aware	Yes (routes, pages, auth)	AST only	No
Schema-aware	Yes (Prisma)	No	No
CI-friendly	Yes (exit codes)	No	No
Human-readable	Excellent	Requires queries	Poor (wall of text)
Git-friendly	Yes (meaningful diffs)	No (binary DB)	Poor (single file)

Try It

npx fondamenta-archcode analyze
npx fondamenta-archcode agents --free

GitHub: github.com/talionwar/fondamenta-archcode
npm: npmjs.com/package/fondamenta-archcode

Currently supports Next.js App Router + Prisma. Multi-framework support (Nuxt, SvelteKit, Remix) is on the roadmap.

Feedback and contributions welcome!

I built a zero-dependency alternative to GitNexus for AI-assisted coding

Cyber Audio Mind — Tue, 24 Feb 2026 02:07:39 +0000

The Problem

Every AI coding tool — Claude Code, Cursor, Copilot — needs to understand your codebase. But they don't. Not really.

They see individual files, but miss the big picture: which components depend on what, how API routes connect to database models, what auth pattern each page uses.

I wanted something simpler.

The Solution: Structured Markdown

Fondamenta ArchCode runs static analysis on your codebase and generates structured Markdown files. That's it.

npx fondamenta-archcode analyze

No database. No server. No runtime dependencies. Just .md files that any LLM can read natively.

What It Generates

.planning/
├── DEPENDENCY-MAP.md          # Architecture overview, impact areas
└── dependencies/
    ├── pages-atomic.md        # Every page: imports, auth, data fetching
    ├── components-atomic.md   # Every component: props, state, hooks, used-by
    ├── api-routes-atomic.md   # Every API route: methods, auth, models
    ├── lib-atomic.md          # Every utility: exports, imports, env vars
    ├── schema-crossref-atomic.md  # DB models, fields, relations, enums
    └── component-graph.md     # Visual dependency tree

Example: pages-atomic.md

### `/dashboard`

- **File:** `app/(dashboard)/dashboard/page.tsx`
- **Type:** Server Component
- **Auth:** auth()
- **Data Fetching:**
  - DB: findMany (courses)
  - DB: count (flashcards)
- **Components:** CourseCard, StatsWidget, RecentActivity

Every AI agent understands this format instantly. No special tools needed.

How It Works

Discovers files using fast-glob (respects .gitignore)
Parses TypeScript/TSX using the TypeScript Compiler API (not regex!)
Builds an in-memory graph of imports, exports, components, hooks
Classifies each file: page, component, API route, lib, hook
Analyzes Prisma schema for models, fields, and relations
Generates structured Markdown with consistent formatting

The TypeScript Compiler API is key here — it gives us a real AST, not fragile regex patterns. We can detect server vs client components, extract hooks, find API calls, and trace the full dependency tree.

Real-World Results

Tested on a 1000+ file Next.js project:

Metric	Count
Pages analyzed	116
Components mapped	487
API routes documented	291
DB models cross-referenced	109
Total time	< 3 seconds

Beyond `analyze`: Full Workflow

# Detect what changed since last analysis
fondamenta diff
fondamenta diff --ci    # Exit code 1 if outdated (for CI pipelines)

# Watch mode — regenerate on file changes
fondamenta watch

# Generate AI context files
fondamenta ai-context --claude   # CLAUDE.md
fondamenta ai-context --cursor   # .cursorrules
fondamenta ai-context --copilot  # copilot-instructions.md
fondamenta ai-context --all      # All of the above

vs Alternatives

	Fondamenta ArchCode	GitNexus	Repomix
Output	Structured .md files	Graph DB (KuzuDB)	Single concatenated file
Runtime deps	None	KuzuDB + MCP server	None
AI integration	Any tool (reads files)	Claude Code only (MCP)	Any tool
Framework-aware	Yes (routes, pages, auth)	AST only	No
Schema-aware	Yes (Prisma)	No	No
Human-readable	Excellent	Requires queries	Poor (wall of text)
Git-friendly	Yes (meaningful diffs)	No (binary DB)	Poor (single file)

Try It

npx fondamenta-archcode analyze

GitHub: github.com/talionwar/fondamenta-archcode
npm: npmjs.com/package/fondamenta-archcode

Currently supports Next.js App Router + Prisma. Multi-framework support (Nuxt, SvelteKit, Remix) is on the roadmap.

Feedback and contributions welcome!

DEV Community: Cyber Audio Mind

I built code health agents that run on your dependency graph — no database, just Markdown

The Problem

The Solution: Structured Markdown + Code Health Agents

What It Generates

Example: pages-atomic.md

Code Health Agents (NEW in v0.3.0)

3 Free Agents

5 PRO Agents (license-gated)

CI Integration

How It Works

Real-World Results

Full Command Set

vs Alternatives

Try It

I built a zero-dependency alternative to GitNexus for AI-assisted coding

The Problem

The Solution: Structured Markdown

What It Generates

Example: pages-atomic.md

How It Works

Real-World Results

Beyond analyze: Full Workflow

vs Alternatives

Try It

Beyond `analyze`: Full Workflow