agentleFS
MovGP0MovGP0/Skills/understand-chat/SKILL.md

understand-chat

Skill1 starsChanged 4 months agoMITView on GitHub

Use when you need to ask questions about a codebase or understand code using a knowledge graph

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 3 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use Grep to search within the JSON for relevant entries BEFORE reading the full file

    line 27
  2. Distinctive:

    Only read sections you need — don't dump the entire graph into context

    line 28
  3. Very specific:

    Check that .understand-anything/knowledge-graph.json exists in the current project root.

    line 34
  4. Very specific:

    Search "name" fields: grep -i "query_keyword" in the graph file

    line 39
  5. Very specific:

    Search "summary" fields for semantic matches

    line 40
  6. Very specific:

    Search "tags" arrays for topic matches

    line 41
  7. Distinctive:

    If the query doesn't match any nodes, say so and suggest related terms from the graph

    line 55

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

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