Build or refresh the Sprang knowledge graph for this workspace. Use when the user says "/sprang", "build the knowledge graph", "scan the codebase", "index this project", or "run sprang".
Instalação
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Build or refresh the Sprang knowledge graph for this workspace. Use when the user says "/sprang", "build the knowledge graph", "scan the codebase", "index this project", or "run sprang".
Check if .sprang/knowledge-graph.json exists — note its generated_at, phase, and kind (codebase or knowledge).
Detect what to analyze:
If the target directory has source code (.ts, .py, .go, .rs, etc.) → run /sprang-analyze for full LLM-driven codebase analysis.
If it contains primarily markdown notes (.md, Obsidian vault, Logseq, Zettelkasten) → run /sprang-knowledge for note graph analysis.
If both → ask the user which they want.
For codebase: run npx @faviovazquez/sprang scan $ARGUMENTS (use cwd if no args) to produce the skeleton graph (<60s), then follow /sprang-analyze for full enrichment.
For knowledge base: follow /sprang-knowledge directly — no CLI prerequisite needed.
Read .sprang/SPRANG_REPORT.md and display key findings.
Report: nodes created, edges, top insights, smells detected (codebase) or top connected notes (knowledge).
Suggest next steps: /sprang-onboard (codebase tour), /sprang-chat (ask questions), /sprang-diff (blast radius before commits), or open dashboard with pnpm --filter @sprang/dashboard dev.
