agentic-actions-audito…
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI,…
Generates Mermaid diagrams from Trailmark code graphs. Produces call graphs, class hierarchies, module dependency maps, containment diagrams, complexity heatmaps, and attack surface data flow visualizations. Use when visualizing code architecture, drawing call graphs, generating
Claude Code
$ npx -y skills add trailofbits/skills --skill diagramming-code --agent claude-code
Codex
$ npx skills add trailofbits/skills --skill diagramming-code -a codex -y
Cursor
$ npx skills add trailofbits/skills --skill diagramming-code -a cursor -y
Gemini CLI
$ npx skills add trailofbits/skills --skill diagramming-code -a gemini-cli -y
GitHub Copilot
$ npx skills add trailofbits/skills --skill diagramming-code -a github-copilot -y
OpenCode
$ npx skills add trailofbits/skills --skill diagramming-code -a opencode -y
Windsurf
$ npx skills add trailofbits/skills --skill diagramming-code -a windsurf -y
name: diagramming-code description: > Generates Mermaid diagrams from Trailmark code graphs. Produces call graphs, class hierarchies, module dependency maps, containment diagrams, complexity heatmaps, and attack surface data flow visualizations. Use when visualizing code architecture, drawing call graphs, generating class diagrams, creating dependency maps, producing complexity heatmaps, or visualizing data flow and attack surface paths as Mermaid diagrams.
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.
**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.
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.
---
uv run {baseDir}/scripts/diagram.py \
--target {targetDir} --language auto --type call-graph \
--focus <function> --depth 2
# Trailmark 0.4.0+ equivalent after the Version Gate succeeds
uv run trailmark diagram \
--target {targetDir} --language auto --type call-graph \
--focus <function> --depth 2Output 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](references/diagram-types.md). --- ## Workflow
Diagram Progress:
**Step 1:** Run `uv run trailmark analyze --language auto --summary {targetDir}`. Install
if it fails. Do not run `engine.preanalysis()` for a diagram: the diagram
command builds its own graph and does not use pre-analysis data, so every
diagram type is identical with or without it. `data-flow` uses the
entrypoints Trailmark records while parsing.
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](references/mermaid-syntax.md).
**Step 6:** Wrap output in ` ```mermaid ``` ` code fence.
---
## Script Referenceuv run {baseDir}/scripts/diagram.py [OPTIONS]
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
```bash
# Call graph centered on a function
uv run {baseDir}/scripts/diagram.py -t src/ -l auto -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/ -l auto -T module-deps --direction LR
# Class members
uv run {baseDir}/scripts/diagram.py -t src/ -l auto -T containment
# Complexity heatmap (threshold 5)
uv run {baseDir}/scripts/diagram.py -t src/ -l auto -T complexity --threshold 5
# Data flow from entrypoints to a specific function
uv run {baseDir}/scripts/diagram.py -t src/ -l auto -T data-flow -f execute_query---
**Direction:** Use `TB` (default) for hierarchical views, `LR` for left-to-right flows like dependency chains.
**Depth:*
Trail of Bits skills and plugins for AI-assisted security analysis, testing, and development. Install this marketplace in Claude Code or Codex, or import it into your ChatGPT workspace marketplace.
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