Receber por email
← Voltar para o catálogo

understand-chat

Use quando precisar fazer perguntas sobre uma base de código ou entender código usando um grafo de conhecimento.

64.4kestrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

Como adicionar

/plugin marketplace add Lum1104/Understand-Anything

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

[![Skillteca](https://www.skillteca.com.br/api/badge/understand-chat/svg)](https://www.skillteca.com.br/skills/understand-chat)

Skills relacionadas

Ver todas de Pesquisa e Web →

Alerta por categoria

Receba novas skills de Pesquisa e Web toda segunda

1 email curto, só com as skills novas de Pesquisa e Web. 4 minutos de leitura, sem spam, cancela com 1 clique.

Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.

Ler descrição completa

/understand-chat

Answer questions about this codebase using the knowledge graph at .understand-anything/knowledge-graph.json.

Graph Structure Reference

The knowledge graph JSON has this structure:

  • project — {name, description, languages, frameworks, analyzedAt, gitCommitHash}
  • nodes[] — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
  • Code node types: file, function, class, module, concept
  • Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource
  • Domain/knowledge node types: domain, flow, step, article, entity, topic, claim, source
  • IDs use the node type as prefix, e.g. file:path, function:path:name, config:path, article:path
  • edges[] — each has {source, target, type, direction, weight}
  • Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites
  • layers[] — each has {id, name, description, nodeIds[]}
  • tour[] — each has {order, title, description, nodeIds[]}

How to Read Efficiently

  1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file
  2. Only read sections you need — don't dump the entire graph into context
  3. Node names and summaries are the most useful fields for understanding
  4. Edges tell you how components connect — follow imports and calls for dependency chains

Instructions

  1. Check that .understand-anything/knowledge-graph.json exists in the current project root. If not, tell the user to run /understand first.
  1. Read project metadata only — use Grep or Read with a line limit to extract just the "project" section from the top of the file for context (name, description, languages, frameworks).
  1. Search for relevant nodes — use Grep to search the knowledge graph file for the user's query keywords: "$ARGUMENTS"
  2. Search "name" fields: grep -i "query_keyword" in the graph file
  3. Search "summary" fields for semantic matches
  4. Search "tags" arrays for topic matches
  5. Note the id values of all matching nodes
  1. Find connected edges — for each matched node ID, Grep for that ID in the edges section to find:
  2. What it imports or depends on (downstream)
  3. What calls or imports it (upstream)
  4. This gives you the 1-hop subgraph around the query
  1. Read layer context — Grep for "layers" to understand which architectural layers the matched nodes belong to.
  1. Answer the query using only the relevant subgraph:
  2. Reference specific files, functions, and relationships from the graph
  3. Explain which layer(s) are relevant and why
  4. Be concise but thorough — link concepts to actual code locations
  5. If the query doesn't match any nodes, say so and suggest related terms from the graph
Compartilhar X LinkedIn