From trailmark
Generates Mermaid diagrams from Trailmark code graphs for visualizing code architecture, call graphs, class hierarchies, dependency maps, complexity heatmaps, and data flow.
How this skill is triggered — by the user, by Claude, or both
Slash command
/trailmark:diagramming-codeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generates Mermaid diagrams from Trailmark's code graph. A pre-made script
Generates Mermaid diagrams from Trailmark's code graph. A pre-made script handles Mermaid syntax generation; Claude selects the diagram type and parameters.
trailmark skill)genotoxic skill)trailmark must be installed. If uv run trailmark fails, run:
uv pip install trailmark
DO NOT fall back to hand-writing Mermaid from source code reading. The script uses Trailmark's parsed graph for accuracy. If installation fails, report the error to the user.
uv run {baseDir}/scripts/diagram.py \
--target {targetDir} --type call-graph \
--focus main --depth 2
Output is raw Mermaid text. Wrap in a fenced code block:
```mermaid
flowchart TB
...
```
├─ "Who calls what?" → --type call-graph
├─ "Class inheritance?" → --type class-hierarchy
├─ "Module dependencies?" → --type module-deps
├─ "Class members and structure?" → --type containment
├─ "Where is complexity highest?" → --type complexity
└─ "Path from input to function?" → --type data-flow
For detailed examples of each type, see references/diagram-types.md.
Diagram Progress:
- [ ] Step 1: Verify trailmark is installed
- [ ] Step 2: Identify diagram type from user request
- [ ] Step 3: Determine focus node and parameters
- [ ] Step 4: Run diagram.py script
- [ ] Step 5: Verify output is non-empty and well-formed
- [ ] Step 6: Embed diagram in response
Step 1: Run uv run trailmark analyze --summary {targetDir}. Install
if it fails. Then run pre-analysis via the programmatic API:
from trailmark.query.api import QueryEngine
engine = QueryEngine.from_directory("{targetDir}", language="{lang}")
engine.preanalysis()
Pre-analysis enriches the graph with blast radius, taint propagation,
and privilege boundary data used by data-flow diagrams.
Step 2: Match the user's request to a --type using the decision tree
above.
Step 3: For call-graph and data-flow, identify the focus function.
Default --depth 2. Use --direction LR for dependency flows.
Step 4: Run the script and capture stdout.
Step 5: Check: output starts with flowchart or classDiagram,
contains at least one node. If empty or malformed, consult
references/mermaid-syntax.md.
Step 6: Wrap output in ```mermaid ``` code fence.
uv run {baseDir}/scripts/diagram.py [OPTIONS]
| Argument | Short | Default | Description |
|---|---|---|---|
--target | -t | required | Directory to analyze |
--language | -l | python | Source language |
--type | -T | required | Diagram type (see above) |
--focus | -f | none | Center diagram on this node |
--depth | -d | 2 | BFS traversal depth |
--direction | TB | Layout: TB (top-bottom) or LR (left-right) | |
--threshold | 10 | Min complexity for complexity type |
# Call graph centered on a function
uv run {baseDir}/scripts/diagram.py -t src/ -T call-graph -f parse_file
# Class hierarchy for a Rust project
uv run {baseDir}/scripts/diagram.py -t src/ -l rust -T class-hierarchy
# Module dependency map, left-to-right
uv run {baseDir}/scripts/diagram.py -t src/ -T module-deps --direction LR
# Class members
uv run {baseDir}/scripts/diagram.py -t src/ -T containment
# Complexity heatmap (threshold 5)
uv run {baseDir}/scripts/diagram.py -t src/ -T complexity --threshold 5
# Data flow from entrypoints to a specific function
uv run {baseDir}/scripts/diagram.py -t src/ -T data-flow -f execute_query
Direction: Use TB (default) for hierarchical views, LR for
left-to-right flows like dependency chains.
Depth: Increase --depth to see more of the call graph. Decrease to
reduce clutter. The script warns if the diagram exceeds 100 nodes.
Focus: Always use --focus for call-graph on non-trivial codebases.
For data-flow, omitting focus auto-targets the top 10 complexity hotspots.
3plugins reuse this skill
First indexed Jul 18, 2026
npx claudepluginhub daothinh/spec-cdex --plugin trailmarkGenerates Mermaid diagrams from Trailmark code graphs for visualizing code architecture, call graphs, class hierarchies, dependency maps, complexity heatmaps, and data flow.
Generates Mermaid class diagrams from codebases to visualize types, inheritance, and composition. Useful for understanding class hierarchies and documenting module public APIs.
Generates Mermaid diagrams (flowcharts, class, sequence, ER) from code for architecture visualization. Keeps docs current.