autojanet/skills/understand-explain/SKILL.md
Zoë cc74ad0bd0
Some checks failed
ci/woodpecker/push/woodpecker Pipeline failed
fix: use library/ Harbor project, add skills, fix pipeline secrets
- .woodpecker.yaml: image paths -> library/autojanet-{agent,dispatcher}
- .woodpecker.yaml: secret names RS_HARBOR_USER / RS_HARBOR_PASS (global)
- container/Dockerfile: restore COPY skills/, skills/ populated from opencode config
- skills/: 84 opencode skills bundled into image
- k8s/manifests: update image refs to library/
2026-05-30 15:43:14 -07:00

3.3 KiB

name description argument-hint
understand-explain Use when you need a deep-dive explanation of a specific file, function, or module in the codebase
file-path

/understand-explain

Provide a thorough, in-depth explanation of a specific code component.

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. If not, tell the user to run /understand first.

  2. Find the target node — use Grep to search the knowledge graph for the component: "$ARGUMENTS"

    • For file paths (e.g., src/auth/login.ts): search for "filePath" matches
    • For function notation (e.g., src/auth/login.ts:verifyToken): search for the function name in "name" fields filtered by the file path
    • Note the exact node id, type, summary, tags, and complexity
  3. Find all connected edges — Grep for the target node's ID in the edges section:

    • "source" matches → things this node calls/imports/depends on (outgoing)
    • "target" matches → things that call/import/depend on this node (incoming)
    • Note the connected node IDs and edge types
  4. Read connected nodes — for each connected node ID from step 3, Grep for those IDs in the nodes section to get their name, summary, and type. This builds the component's neighborhood.

  5. Identify the layer — Grep for the target node's ID in the "layers" section to find which architectural layer it belongs to and that layer's description.

  6. Read the actual source file — Read the source file at the node's filePath for the deep-dive analysis.

  7. Explain the component in context:

    • Its role in the architecture (which layer, why it exists)
    • Internal structure (functions, classes it contains — from contains edges)
    • External connections (what it imports, what calls it, what it depends on — from edges)
    • Data flow (inputs → processing → outputs — from source code)
    • Explain clearly, assuming the reader may not know the programming language
    • Highlight any patterns, idioms, or complexity worth understanding