/supergraph:explore

SkillDev tools

Deep codebase exploration, architectural research, and solution discovery. Use when investigating problems, understanding complex flows, or evaluating technical approaches without jumping straight into code mutation or TDD.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the /supergraph:explore skill

What this skill tells your AI

The instructions your AI receives, as published by datit309/supergraph in plugins/supergraph/skills/explore/SKILL.md and read by ahel’s review.

Investigate first. Understand deeply. No unwanted code modification.

Announce: "🧭 /supergraph:explore — investigating codebase and tracing flows..."

When to Use

  • Understanding an existing feature, module, or architecture
  • Tracing end-to-end request/event lifecycles (UI → BLoC/Service → API → DB)
  • Investigating bug symptoms before declaring a fix approach
  • Evaluating libraries, architectural options, or technical trade-offs
  • Onboarding to a new workspace or subsystem

Workflow

1. Define Research Scope

  • Subject: What system, flow, or question is being investigated?
  • Boundaries: Known entry points, affected modules, or target concepts.
  • Target Output: Architecture overview, flow diagram, root cause analysis, or comparison matrix.

2. Semantic & Graph Discovery

  • High-level map: Use get_architecture(project=CBM_PROJECT) or /zoom-out to orient.
  • Symbol / Route discovery: Use Serena find_symbol, get_symbols_overview or Codebase Memory search_graph.
  • Trace connections: Use trace_path or Serena find_referencing_symbols / find_implementations to identify callers, callees, and data flow.

3. Targeted Source Deep-Dive

  • Inspect the actual code files for key components (controller, service, repository, UI state).
  • Read method implementations directly when business logic, validations, or transformations matter.
  • Target reading precisely: understanding requires seeing concrete implementations, not just graph nodes.

4. Trace the Flow End-to-End

Trace the execution path:

  1. Entry Point: HTTP route handler, UI widget event, CLI command, or queue consumer.
  2. Middleware / Guards: Authentication, validation, rate limiting, interceptors.
  3. Domain Logic / Orchestration: Service layer, state management, entity calculations.
  4. Data / External I/O: Database queries, external API calls, cache lookups.
  5. Output / Side Effects: Response serialization, state updates, event emissions.

5. Synthesize & Report Findings

Present findings in clear, structured Markdown:

  • Executive Summary: 2-3 sentences explaining how it works or what the finding is.
  • Flow Diagram: ASCII or Mermaid sequence/flowchart.
  • Key Files & Responsibilities: Table of files with their exact role.
  • Critical Invariants & Edge Cases: Hidden assumptions, potential pitfalls, race conditions.
  • Recommendations: If leading into implementation, outline next steps (/plan, /analyze, or /prototype).

Signals

GitHub stars
22
Forks
6
Last commit
Sep 2026
Hacker News mentions
20
Advanced
Item type
skill
Key
explore-datit309
Source
github.com/datit309/supergraph