Skip to content
cccskills
FreePublished on GitHub

living-codebase-ast-graph

Expert guide for in-memory Abstract Syntax Tree (AST) code knowledge graphs, real-time symbol dependency mapping, refactoring blast radius calculation, and dead code eradication / Panduan ahli graf pengetahuan AST kode in-memory, pemetaan dependensi simbol real-time, kalkulasi radius dampak refaktor, dan pembersihan kode mati.

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md11.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

living-codebase-ast-graph — vibes-plug Skill

English | Bahasa Indonesia


<a name="english"></a>

English

Orchestration & Integration

Connects and orchestrates with brainstorming, zero-to-prod-orchestrator, typescript-expert, scalability-clean-code, zero-tech-debt-auditor, and autonomous-api-drift-healer to provide real-time AST dependency graphs, blast-radius calculation, and structural intelligence for multi-agent code transformations.

Description

Production guide for constructing and querying in-memory Abstract Syntax Tree (AST) knowledge graphs across multi-file and monorepo codebases. Enables autonomous agents to navigate complex symbol relationships, calculate refactoring blast radii, eliminate circular dependencies, determine optimal topological generation sequences, and prune unreachable code without relying on fuzzy string matching.

Trigger Conditions

Activate this skill when:

  • Executing large-scale codebase refactoring or renaming symbols across multiple packages.
  • Analyzing architectural blast radius before making breaking changes to data models or API signatures.
  • Detecting and resolving circular dependencies in TypeScript, JavaScript, Python, or Go codebases.
  • Ordering code generation tasks topologically so underlying dependencies are created before dependent modules.
  • Identifying dead exports, unreferenced functions, and ghost imports with absolute precision.

Core Concepts & Patterns

1. In-Memory AST Dependency Extractor (TypeScript Compiler API)

import ts from 'typescript';
import fs from 'fs';
import path from 'path';

export interface SymbolNode {
  filePath: string;
  name: string;
  kind: 'function' | 'class' | 'interface' | 'variable' | 'type';
  dependencies: string[];
}

export interface CodebaseGraph {
  nodes: Map<string, SymbolNode>;
  edges: Map<string, Set<string>>;
}

export class LivingCodebaseASTGraph {
  private program: ts.Program;
  private checker: ts.TypeChecker;
  private graph: CodebaseGraph;

  constructor(rootFiles: string[], options: ts.CompilerOptions = {}) {
    this.program = ts.createProgram(rootFiles, {
      target: ts.ScriptTarget.ES2022,
      module: ts.ModuleKind.NodeNext,
      ...options
    });
    this.checker = this.program.getTypeChecker();
    this.graph = {
      nodes: new Map(),
      edges: new Map()
    };
    this.buildGraph();
  }

  private buildGraph(): void {
    for (const sourceFile of this.program.getSourceFiles()) {
      if (sourceFile.isDeclarationFile || sourceFile.fileName.includes('node_modules')) {
        continue;
      }
      this.analyzeSourceFile(sourceFile);
    }
  }

  private analyzeSourceFile(sourceFile: ts.SourceFile): void {
    const filePath = path.resolve(sourceFile.fileName);

    ts.forEachChild(sourceFile, (node) => {
      if (ts.isFunctionDeclaration(node) && node.name) {
        this.registerSymbol(filePath, node.name.text, 'function', node);
      } else if (ts.isClassDeclaration(node) && node.name) {
        this.registerSymbol(filePath, node.name.text, 'class', node);
      } else if (ts.isInterfaceDeclaration(node) && node.name) {
        this.registerSymbol(filePath, node.name.text, 'interface', node);
      }
    });
  }

  private registerSymbol(
    filePath: string,
    name: string,
    kind: SymbolNode['kind'],
    node: ts.Node
  ): void {
    const symbolKey = `${filePath}#${name}`;
    const dependencies: string[] = [];

    const visit = (child: ts.Node) => {
      if (ts.isIdentifier(child)) {
        const symbol = this.checker.getSymbolAtLocation(child);
        if (symbol && symbol.declarations && symbol.declarations.length > 0) {
          const declFile = symbol.declarations[0].getSourceFile().fileName;
          if (!declFile.includes('node_modules') && !declFile.endsWith('.d.ts')) {
            const targetKey = `${path.resolve(declFile)}#${symbol.getName()}`;
            if (targetKey !== symbolKey) {
              dependencies.push(targetKey);
            }
          }
        }
      }
      ts.forEachChild(child, visit);
    };

    visit(node);

    this.graph.nodes.set(symbolKey, { filePath, name, kind, dependencies });
    if (!this.graph.edges.has(symbolKey)) {
      this.graph.edges.set(symbolKey, new Set(dependencies));
    }
  }

  public calculateBlastRadius(symbolKey: string): string[] {
    const affected = new Set<string>();
    const queue = [symbolKey];

    while (queue.length > 0) {
      const current = queue.shift()!;
      for (const [nodeKey, deps] of this.graph.edges.entries()) {
        if (deps.has(current) && !affected.has(nodeKey)) {
          affected.add(nodeKey);
          queue.push(nodeKey);
        }
      }
    }
    return Array.from(affected);
  }
}

2. Topological Code Generation Sorter

Autonomous swarms must construct files in strict topological order to avoid compiling against non-existent types:

[Core Domain Types / Schemas]
             │
             ▼
[Persistence Layer & ORM Repositories]
             │
             ▼
[Business Services & Interactors]
             │
             ▼
[API Handlers / Controllers]
             │
             ▼
[Client SDKs & Frontend Hooks]

Best Practices

  1. Reject String RegEx for Semantic Audits: Never use regex or text matching to find symbol usages; use static AST symbol declarations.
  2. Compute Blast Radius Before Refactoring: When a core database model or API payload changes, compute all affected frontend and backend nodes first.
  3. Fail Builds on Circular Dependencies: Integrate AST cycle checks directly into continuous integration pipelines to prevent runtime initialization deadlocks.
  4. Order Swarm Generation Topologically: Feed code generation tasks to subagents according to dependency levels so downstream callers always receive complete interfaces.

Common Pitfalls to Avoid

Anti-PatternBlast ConsequenceCorrect AST Engineering
Global find-and-replace for variable renamingCorrupts unrelated variables sharing identical namesUse AST symbol binding via ts.TypeChecker
Parallel multi-file generation without topological sortSubagent attempts to import interfaces that do not existSequence subagents using Directed Acyclic Graph (DAG) levels
Ignoring circular module referencesSilent runtime initialization undefined bugsTraverse graph using Tarjan's SCC algorithm

Integration with Other Skills (MANDATORY)

  • typescript-expert — Provide low-level TypeScript AST manipulation and type checking APIs.
  • zero-tech-debt-auditor — Feed dead symbol lists to the automated dead code elimination pipeline.
  • autonomous-api-drift-healer — Calculate client-side impact when backend API contracts drift.
  • scalability-clean-code — Enforce Clean Architecture boundary rules between modules.

Referenced By Orchestrators (MANDATORY)

  • brainstorming — Added to "Arsitektur & Skala" and "Penemuan & Audit" matrix rows.
  • zero-to-prod-orchestrator — Integrated in Phase 2 (Foundation) and Phase 6 (Testing & QA).

<a name="bahasa-indonesia"></a>

Bahasa Indonesia

Integrasi Orkestrasi

Terhubung dan mengorkestrasi dengan brainstorming, zero-to-prod-orchestrator, typescript-expert, scalability-clean-code, zero-tech-debt-auditor, dan autonomous-api-drift-healer untuk menyediakan graf dependensi AST real-time, kalkulasi radius dampak refaktor, dan inteligensi struktural untuk transformasi kode multi-agen.

Deskripsi

Panduan produksi untuk membangun dan menavigasi graf pengetahuan Abstract Syntax Tree (AST) in-memory pada proyek perangkat lunak berskala besar dan monorepo. Memungkinkan agen otonom untuk memahami relasi simbolik, menghitung radius dampak (blast radius) sebelum refaktor, mendeteksi dependensi melingkar (circular dependency), menentukan urutan pembuatan kode secara topologis, dan membersihkan kode mati tanpa mengandalkan pencarian teks biasa.

Kondisi Pemicu

Aktifkan skill ini ketika:

  • Menjalankan refaktor skala besar atau mengganti nama simbol di banyak file/paket.
  • Menganalisis radius dampak arsitektur sebelum mengubah skema database atau kontrak API.
  • Mendeteksi dan memecahkan dependensi melingkar (circular dependency).
  • Menentukan urutan pembuatan kode bagi sub-agen secara topologis agar dependensi dasar dibuat terlebih dahulu.
  • Mengidentifikasi export yang tidak lagi dipakai (dead code) dan impor phantom.

Konsep Inti & Pola Praktik

1. Kalkulasi Radius Dampak (Blast Radius)

Saat mengubah suatu fungsi inti atau tipe data:

  1. Identifikasi Simbol: Dapatkan simpul AST target menggunakan ts.TypeChecker.
  2. Penelusuran Graf Terbalik: Telusuri semua simpul yang mengimpor atau memanggil simbol tersebut secara rekursif.
  3. Pemberian Skor Risiko: Klasifikasikan file yang terdampak ke dalam tingkat risiko (Tinggi untuk API publik, Sedang untuk modul internal).

2. Urutan Pembangunan Topologis untuk Swarm

Pastikan sub-agen AI membangun file berdasarkan tingkatan hierarki DAG:

  • Tingkat 0: Skema Database & Tipe Inti
  • Tingkat 1: Repositori Data & ORM
  • Tingkat 2: Layanan Logika Bisnis (Services)
  • Tingkat 3: Endpoint Controller & API Route
  • Tingkat 4: Hooks Frontend & Komponen UI

Praktik Terbaik

  1. Gunakan AST Bukan Regex: Hindari pencarian teks biasa (find-and-replace) yang dapat merusak variabel bernama serupa di berkas lain.
  2. Hitung Radius Dampak Sebelum Memulai: Sebelum sub-agen menulis ulang kode, dapatkan daftar lengkap berkas yang bergantung padanya.
  3. Cegah Dependensi Melingkar: Jalankan algoritma Tarjan atau DFS untuk memastikan tidak ada siklus dependensi yang menyebabkan nilai undefined saat runtime.
  4. Hapus Kode Mati Secara Otomatis: Padukan dengan zero-tech-debt-auditor untuk membersihkan fungsi dan tipe yang tidak memiliki referensi masuk (inbound edges).

Jebakan Umum yang Harus Dihindari

Praktik BurukDampak BurukSolusi Rekayasa
Mengganti nama fungsi dengan string replace biasaMerusak properti objek atau komentar yang kebetulan memiliki nama yang samaGunakan binding simbol AST dari TypeScript Compiler API
Memerintahkan sub-agen membuat UI sebelum tipe data siapMuncul error tipe hilang dan kompilasi gagalSusun urutan pembuatan secara topologis (Topological Sort)
Membiarkan import melingkar (circular imports)Bug runtime sulit dilacak saat aplikasi diinisialisasiLakukan pengecekan siklus AST pada CI pipeline

Integrasi dengan Skill Lain (WAJIB)

  • typescript-expert — Manipulasi AST tingkat lanjut dan pemeriksaan tipe TypeScript.
  • zero-tech-debt-auditor — Menyuplai daftar ekspor mati ke pipeline pembersihan kode.
  • autonomous-api-drift-healer — Menghitung dampak pada sisi klien saat kontrak API backend berubah.
  • scalability-clean-code — Menegakkan batas arsitektur bersih antar modul.

Direferensikan oleh Orchestrator (WAJIB)

  • brainstorming — Tambahkan ke baris "Arsitektur & Skala" dan "Penemuan & Audit" pada Matriks Orkestrasi.
  • zero-to-prod-orchestrator — Tambahkan ke Fase 2 (Pondasi Proyek) dan Fase 6 (Pengujian Otomatis & Keamanan).

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Expert guide for automated and manual Web Accessibility (a11y) testing — axe-core, Pa11y, Playwright a11y, screen reader testing, and WCAG 2.2 Level AA/AAA compliance / Panduan ahli pengujian aksesibilitas web.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

Expert guide for intelligent model cascading and routing — complexity-scored task routing from Flash/Haiku to Sonnet/Opus/Astra, dynamic escalation with quality gates, 40-60% token cost reduction while maintaining output quality / Panduan ahli untuk kaskade dan routing model cerdas — routing tugas berbasis skor kompleksitas dari Flash/Haiku ke Sonnet/Opus/Astra, eskalasi dinamis dengan gerbang kualitas, pengurangan biaya token 40-60% dengan kualitas output terjaga.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

Expert guide for Affective Computing, emotional AI, and real-time sentiment analysis through native multimodal tokens (voice intonation and facial micro-expressions) / Panduan ahli komputasi afektif, AI emosional, dan analisis sentimen real-time melalui token multimodal native.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

Expert guide for AI-assisted coding workflows — agentic code generation, multi-agent code swarms, self-healing CI/CD, automated PR review, spec-to-code pipelines, codebase knowledge graphs, and human-in-the-loop approval gates / Panduan ahli untuk workflow pengkodean berbasis AI — generasi kode agentic, code swarm multi-agen, CI/CD self-healing, review PR otomatis, pipeline spec-to-code, knowledge graph codebase, dan gate persetujuan human-in-the-loop.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

Expert guide for autonomous Machine-to-Machine (M2M) agent settlement, dual-rail fiat & stablecoin micro-clearing, dynamic budget envelopes, and cryptographic agent invoicing / Panduan ahli settlement otonom antar-agen (M2M), kliring mikro dual-rail fiat & stablecoin, pagu anggaran dinamis, dan penagihan agen kriptografis.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

Expert guide for long-term episodic memory integration (Mem0 v2, Letta/MemGPT, Zep v2), memory tier architecture, pgvector HNSW storage, and unified context management for autonomous AI agents / Panduan ahli untuk integrasi memori episodik jangka panjang (Mem0 v2, Letta/MemGPT, Zep v2), arsitektur tier memori, penyimpanan pgvector HNSW, dan manajemen konteks terpadu untuk agen AI otonom.

The English summary is being prepared. Showing the original description.

roedyrustam/vibes-plug105Updated Oct 20, 2026

See all skills by roedyrustam

Report a problem with this skill