Claude-skill-registry hierarchy-tree
Construct ASCII tree visualizations from parent/child work item data. Use when the user asks to "show hierarchy", "show tree", "display parent child", "visualize structure", "show feature tree", or wants to see work item relationships as a tree diagram. This skill teaches how to build trees from flat data WITHOUT code - use LLM reasoning only.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/hierarchy-tree" ~/.claude/skills/majiayu000-claude-skill-registry-hierarchy-tree && rm -rf "$T"
manifest:
skills/data/hierarchy-tree/SKILL.mdsource content
Building ASCII Trees from Parent/Child Data
When you have flat parent/child data, construct the tree visually using LLM reasoning - NO CODE NEEDED.
Step 1: Get the Data
Query work items with their parent:
az boards query --wiql "SELECT [System.Id], [System.Title] FROM workitems WHERE [System.WorkItemType] = 'Feature' AND [System.TeamProject] = 'ProjectName'" -o json
Then for each item, get its parent via relations (System.LinkTypes.Hierarchy-Reverse).
The result is flat data like:
ID Parent Title 1517 1509 Feature A 1518 1509 Feature B 1759 1827 Feature C 1827 1509 Feature D
Step 2: Build the Tree (LLM Reasoning)
- Find roots - Items whose Parent is not in the ID list (or is an Epic/external)
- Group children - For each ID, collect all items where Parent = that ID
- Recurse - Build subtrees for each child
From the example above:
- Root: 1509 (not in ID list as a child)
- 1509's children: 1517, 1518, 1827
- 1827's children: 1759
Step 3: Render ASCII
Use these characters:
| = vertical continuation (more siblings below) |-- = branch to sibling (more siblings follow) `-- = last branch (no more siblings) = indent (4 spaces under a last branch)
Rules:
- Each level indents 4 characters
- Use
for all children except the last|-- - Use
for the last child`-- - Continue
vertically when parent has more siblings|
Example Transformation
Input data:
ID Parent Name 100 - Root 200 100 Child A 300 100 Child B 400 300 Grandchild B1 500 300 Grandchild B2 600 100 Child C
Output tree:
#100 Root |-- #200 Child A |-- #300 Child B | |-- #400 Grandchild B1 | `-- #500 Grandchild B2 `-- #600 Child C
Complex Example
Input:
ID Parent Name 1 - Epic 10 1 Feature A 11 1 Feature B 20 10 Sub A1 21 10 Sub A2 30 11 Sub B1 31 30 Deep B1a 32 30 Deep B1b
Output:
#1 Epic |-- #10 Feature A | |-- #20 Sub A1 | `-- #21 Sub A2 `-- #11 Feature B `-- #30 Sub B1 |-- #31 Deep B1a `-- #32 Deep B1b
Key Points
- Don't use code - The LLM can construct this from data using reasoning
- Process top-down - Start from roots, recurse into children
- Track "is last" - Determines
vs|--`-- - Track depth - Determines indentation and vertical bars
- Keep it clean - Omit IDs if user prefers names only
When to Use
- User asks for "tree view" or "hierarchy"
- User wants to see parent/child relationships
- Visualizing feature breakdown structures
- Showing Epic → Feature → PBI → Task relationships