Claude Skill

diagramming-code

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

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Part of trailofbits/skills — 100 skills

Install

skills CLI npx skills add https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/diagramming-code
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install trailofbits-skills@llmmart
Git git clone https://github.com/trailofbits/skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole trailofbits/skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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 trailmark skill)
  • Mutation testing triage (use the genotoxic skill)
  • 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

Files (skills)
  • agents
    • openai.yaml 241 B
      interface:
        display_name: "Code Diagrams"
        short_description: "Generate architecture diagrams from Trailmark code graphs"
        icon_small: "assets/trail-of-bits-mark.svg"
        icon_large: "assets/trail-of-bits-mark.svg"
        brand_color: "#D83A34"
      
  • assets
    • trail-of-bits-mark.svg 3 KB · in bundle
  • references
    • diagram-types.md 5.1 KB
      # Diagram Types
      
      ## Contents
      
      - [Call graph](#call-graph)
      - [Class hierarchy](#class-hierarchy)
      - [Module dependencies](#module-dependencies)
      - [Containment](#containment)
      - [Complexity heatmap](#complexity-heatmap)
      - [Attack surface / data flow](#attack-surface--data-flow)
      
      ---
      
      ## Call Graph
      
      Shows which functions call which. Built from `callers_of` / `callees_of`
      queries and `calls` edges.
      
      **Mermaid type:** `flowchart`
      
      **When to use `--focus`:** Almost always. Without focus, large codebases
      produce unreadable diagrams. Start with `--depth 2` and increase if needed.
      
      **Arrow styles reflect edge confidence:**
      - Solid (`-->`) = certain (direct call)
      - Dashed (`-.->`) = inferred (attribute access on non-self)
      - Dotted (`..->`) = uncertain (dynamic dispatch)
      
      **Example output:**
      
      ```mermaid
      flowchart TB
          query_api_QueryEngine_callers_of["callers_of, method"]
          query_api_QueryEngine_callees_of["callees_of, method"]
          query_api_QueryEngine_paths_between["paths_between, method"]
          storage_graph_store_GraphStore_find_node_id["find_node_id, method"]
          query_api_QueryEngine_callers_of --> storage_graph_store_GraphStore_find_node_id
          query_api_QueryEngine_callees_of --> storage_graph_store_GraphStore_find_node_id
          query_api_QueryEngine_paths_between --> storage_graph_store_GraphStore_find_node_id
      ```
      
      **Script invocation:**
      
      ```bash
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type call-graph \
          --focus QueryEngine --depth 2
      ```
      
      ---
      
      ## Class Hierarchy
      
      Shows inheritance (`<|--`) and interface implementation (`<|..`)
      relationships between classes, structs, interfaces, and traits.
      
      **Mermaid type:** `classDiagram`
      
      **Limitations:** Languages without class inheritance (e.g., Go, C) produce
      empty diagrams. The script emits a note node in that case.
      
      **Example output:**
      
      ```mermaid
      classDiagram
          class models_nodes_CodeUnit {
              class
          }
          class models_edges_CodeEdge {
              class
          }
          models_nodes_CodeUnit <|-- models_nodes_Parameter
      ```
      
      **Script invocation:**
      
      ```bash
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type class-hierarchy
      ```
      
      ---
      
      ## Module Dependencies
      
      Shows import relationships between modules. Built from `imports` edges.
      
      **Mermaid type:** `flowchart`
      
      **Best with `--direction LR`** for left-to-right dependency flow.
      
      **Example output:**
      
      ```mermaid
      flowchart LR
          query_api["api, module"]
          storage_graph_store["graph_store, module"]
          models_nodes["nodes, module"]
          query_api --> storage_graph_store
          storage_graph_store --> models_nodes
      ```
      
      **Script invocation:**
      
      ```bash
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type module-deps --direction LR
      ```
      
      ---
      
      ## Containment
      
      Shows classes and their member functions/methods using `contains` edges.
      
      **Mermaid type:** `classDiagram` (with member lists)
      
      **Example output:**
      
      ```mermaid
      classDiagram
          class storage_graph_store_GraphStore {
              +callers_of()
              +callees_of()
              +paths_between() list
              +find_node() CodeUnit
          }
      ```
      
      **Script invocation:**
      
      ```bash
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type containment
      ```
      
      ---
      
      ## Complexity Heatmap
      
      Shows functions color-coded by cyclomatic complexity with call edges
      between them. Only nodes meeting `--threshold` are included.
      
      **Mermaid type:** `flowchart` with `classDef` styles
      
      **Color scale:**
      - Green (`low`): CC < 5
      - Yellow (`medium`): CC 5-10
      - Red (`high`): CC > 10
      
      **Example output:**
      
      ```mermaid
      flowchart TB
          parsers_python_parser_parse_file["parse_file, method, CC=15"]:::high
          parsers_python_parser_visit_class["visit_class, method, CC=8"]:::medium
          parsers_python_parser_parse_file --> parsers_python_parser_visit_class
          classDef low fill:rgba(40,167,69,0.2),stroke:#28a745,color:#28a745
          classDef medium fill:rgba(255,193,7,0.2),stroke:#e6a817,color:#e6a817
          classDef high fill:rgba(220,53,69,0.2),stroke:#dc3545,color:#dc3545
      ```
      
      **Script invocation:**
      
      ```bash
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type complexity --threshold 5
      ```
      
      ---
      
      ## Attack Surface / Data Flow
      
      Shows paths from entrypoints (user input, API endpoints) to sensitive
      functions. Entrypoints are styled distinctly (rounded rectangles, blue).
      
      **Mermaid type:** `flowchart`
      
      Without `--focus`, the script targets the top 10 complexity hotspots
      reachable from entrypoints. With `--focus`, it shows all paths from
      entrypoints to the specified function.
      
      **Example output:**
      
      ```mermaid
      flowchart TB
          handle_request(["handle_request, function"]):::entrypoint
          validate_input["validate_input, function"]
          execute_query["execute_query, function"]
          handle_request --> validate_input
          validate_input --> execute_query
          classDef entrypoint fill:rgba(0,123,255,0.2),stroke:#007bff,color:#007bff
      ```
      
      **Script invocation:**
      
      ```bash
      # Focus on a specific sensitive function
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type data-flow \
          --focus execute_query
      
      # Auto-detect: entrypoints to top complexity hotspots
      uv run {baseDir}/scripts/diagram.py \
          --target {targetDir} --type data-flow
      ```
      
    • mermaid-syntax.md 2.9 KB
      # Mermaid Syntax Reference
      
      Pitfalls and edge cases when generating Mermaid from code graph data.
      
      ## Contents
      
      - [Node ID sanitization](#node-id-sanitization)
      - [Label escaping](#label-escaping)
      - [Style definitions](#style-definitions)
      - [Edge confidence styling](#edge-confidence-styling)
      - [Common pitfalls](#common-pitfalls)
      
      ---
      
      ## Node ID Sanitization
      
      Trailmark node IDs use `module:Class.method` format. Mermaid node IDs
      only allow `[a-zA-Z0-9_]`.
      
      **Rules applied by `diagram.py`:**
      - Replace any non-alphanumeric character (except `_`) with `_`
      - Prefix with `n_` if the result starts with a digit
      
      **Examples:**
      
      | Trailmark ID | Mermaid ID |
      |---|---|
      | `query.api:QueryEngine.callers_of` | `query_api_QueryEngine_callers_of` |
      | `3rdparty:init` | `n_3rdparty_init` |
      
      ---
      
      ## Label Escaping
      
      Node labels are wrapped in double quotes to safely include special
      characters:
      
      ```
          node_id["label with (parens) and: colons"]
      ```
      
      If the label itself contains double quotes, replace `"` with `#quot;`
      (Mermaid's HTML entity escape).
      
      ---
      
      ## Style Definitions
      
      Use `classDef` to define reusable styles and `:::` to apply them:
      
      ```mermaid
      flowchart TB
          A["Low complexity"]:::low
          B["High complexity"]:::high
          classDef low fill:rgba(40,167,69,0.2),stroke:#28a745,color:#28a745
          classDef high fill:rgba(220,53,69,0.2),stroke:#dc3545,color:#dc3545
      ```
      
      The script defines three classes for complexity heatmaps:
      - `low` (green): CC < 5
      - `medium` (yellow): CC 5-10
      - `high` (red): CC > 10
      
      And one for data flow:
      - `entrypoint` (blue): marks untrusted input sources
      
      ---
      
      ## Edge Confidence Styling
      
      Arrow syntax varies by edge confidence:
      
      | Confidence | Arrow | Meaning |
      |---|---|---|
      | `certain` | `-->` | Direct call or `self.method()` |
      | `inferred` | `-.->` | Attribute access on non-self object |
      | `uncertain` | `..->` | Dynamic dispatch, reflection |
      
      For class diagrams, arrows are different:
      - `<\|--` = inherits
      - `<\|..` = implements
      
      ---
      
      ## Common Pitfalls
      
      **Reserved words as node IDs:** `end`, `graph`, `subgraph`, `style`,
      `classDef`, `click` are reserved. The sanitization function avoids most
      conflicts since it replaces special characters, but single-word function
      names matching reserved words can still collide. Workaround: use the full
      qualified ID which includes the module prefix.
      
      **Leading digits:** Mermaid node IDs cannot start with a digit. The
      script prefixes `n_` in this case.
      
      **Diagram size:** Mermaid renderers struggle with >100 nodes. The script
      warns when this limit is exceeded and suggests using `--focus` to scope
      the diagram.
      
      **Empty diagrams:** When no edges of the required type exist (e.g., no
      `inherits` edges in a Go codebase), the script emits a single-node
      diagram with an explanatory message rather than failing.
      
      **Parentheses in labels:** Mermaid interprets `()` as rounded-rectangle
      node shape. Always use quoted labels (`["label"]`) to avoid accidental
      shape changes.
      
  • scripts
    • diagram.py 389 B
      # /// script
      # requires-python = ">=3.12"
      # dependencies = ["trailmark"]
      # ///
      """Generate Mermaid diagrams from Trailmark code graphs.
      
      Thin wrapper — all logic lives in ``trailmark.diagram``.
      Run via ``uv run {this_file} --target ... --type ...``.
      """
      
      from __future__ import annotations
      
      import sys
      
      from trailmark.diagram import main
      
      if __name__ == "__main__":
          sys.exit(main())
      
  • SKILL.md 6.7 KB
    ---
    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.
    ---
    
    # 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 `trailmark` skill)
    - Mutation testing triage (use the `genotoxic` skill)
    - Architecture diagrams not derived from code (draw by hand)
    
    ## Prerequisites
    
    **trailmark** must be installed. If `uv run trailmark` fails, run:
    
    ```bash
    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:
    
    ```bash
    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
    
    ```bash
    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:
    
    ````markdown
    ```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: 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:
    
    ```python
    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](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
    
    ```bash
    # 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](references/diagram-types.md)** -
      Detailed docs and Mermaid examples for each diagram type
    - **[references/mermaid-syntax.md](references/mermaid-syntax.md)** -
      ID sanitization, escaping, style definitions, and common pitfalls
    

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