diagramming-code
About
This skill generates Mermaid diagrams from Trailmark code graphs to visualize software architecture. It creates call graphs, class hierarchies, dependency maps, complexity heatmaps, and attack surface visualizations. Developers should use it when they need to diagram code structure, dependencies, or data flows.
Quick Install
Claude Code
Recommendednpx skills add trailofbits/skills -a claude-code/plugin add https://github.com/trailofbits/skillsgit clone https://github.com/trailofbits/skills.git ~/.claude/skills/diagramming-codeCopy and paste this command in Claude Code to install this skill
Documentation
Diagramming Code
Generates Mermaid diagrams from Trailmark's code graph. A pre-made script
handles Mermaid syntax generation; Claude selects the diagram type and
parameters. Trailmark 0.4.0 includes a native trailmark diagram command; use
it only after a version/command check, otherwise use this skill's bundled
script.
When to Use
- Visualizing call paths between functions
- Drawing class inheritance hierarchies
- Mapping module import dependencies
- Showing class structure with members
- Highlighting complexity hotspots with color coding
- Tracing data flow from entrypoints to sensitive functions
When NOT to Use
- Querying the graph without visualization (use the
trailmarkskill) - Mutation testing triage (use the
genotoxicskill) - Architecture diagrams not derived from code (draw by hand)
Prerequisites
trailmark must be installed. If uv run trailmark fails, run:
uv tool install trailmark
# Python snippets: uv run --with trailmark python - (a tool env is not importable)
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.
Version Gate
Check whether native v0.4 diagram support exists:
trailmark diagram --help 2>/dev/null || uv run trailmark diagram --help 2>/dev/null
If this succeeds, you may use trailmark diagram. If it fails, use
uv run {baseDir}/scripts/diagram.py, which keeps the older skill workflow
intact. Do not assume the native CLI exists on Trailmark 0.2.x.
Quick Start
uv run {baseDir}/scripts/diagram.py \
--target {targetDir} --language auto --type call-graph \
--focus main --depth 2
# Trailmark 0.4.0+ equivalent after the Version Gate succeeds
uv run trailmark diagram \
--target {targetDir} --language auto --type call-graph \
--focus main --depth 2
Output is raw Mermaid text. Wrap in a fenced code block:
```mermaid
flowchart TB
...
```
Diagram Types
├─ "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.
Workflow
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 (or native trailmark diagram on v0.4+)
- [ ] Step 5: Verify output is non-empty and well-formed
- [ ] Step 6: Embed diagram in response
Step 1: Run uv run trailmark analyze --language auto --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="auto")
engine.preanalysis()
Pre-analysis enriches the graph with blast radius, taint propagation,
and privilege boundary data used by data-flow diagrams.
If auto-detection is wrong for the target, rerun with an explicit language or
comma-separated list such as python,rust.
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. If the native v0.4 CLI is available, either command is acceptable; prefer the bundled script when you need behavior consistent with this skill's references.
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.
Script Reference
uv run {baseDir}/scripts/diagram.py [OPTIONS]
# or, on Trailmark 0.4.0+:
uv run trailmark diagram [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 |
Examples
# 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
Customization
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.
Language: Prefer --language auto for polyglot or unfamiliar repos.
Use an explicit language only when you know the target is single-language or
you need to exclude unrelated components.
Supporting Documentation
- references/diagram-types.md - Detailed docs and Mermaid examples for each diagram type
- references/mermaid-syntax.md - ID sanitization, escaping, style definitions, and common pitfalls
GitHub Repository
Frequently asked questions
What is the diagramming-code skill?
diagramming-code is a Claude Skill by trailofbits. Skills package instructions and resources that Claude loads on demand, so Claude can perform diagramming-code-related tasks without extra prompting.
How do I install diagramming-code?
Use the install commands on this page: add diagramming-code to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does diagramming-code belong to?
diagramming-code is in the Meta category.
Is diagramming-code free to use?
Yes. diagramming-code is listed on AIMCP and free to install.
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