<< All versions

Skill v1.0.0

currentAutomated scan100/100
maxidonkey/delphianthropic/delphi-uses-graph
──Details
PublishedOctober 24, 2026 at 06:01 PM
Content Hashsha256:9cb170d96dcd206f...
Git SHA786bb556372a
──Files
Files (1 file, 4.0 KB)
SKILL.md4.0 KBactive
SKILL.md · 85 lines · 4.0 KB

version: "1.0.0" name: delphi-uses-graph description: Analyzes a Delphi / Object Pascal codebase to extract unit-level uses dependencies. Use when the user uploads a zip / archive of a Delphi project (or a folder of .pas / .dpr / .dpk files) and asks for a dependency graph, architecture map, cycle detection, fan-in / fan-out coupling analysis, or wants to know how units relate. Produces a Mermaid diagram, a Graphviz DOT file, an SVG when graphviz is available, a JSON dump of the parsed graph, and a markdown report listing cycles, hotspots and orphan units.

Delphi uses-graph skill

This skill builds a directed graph of uses dependencies between Delphi / Object Pascal units, computes coupling metrics, and detects circular dependencies.

When to use this skill

  • The user uploads an archive (.zip, .tar, .tar.gz) containing a Delphi

project, or a folder of .pas / .dpr / .dpk sources, and asks for an architecture map or a dependency graph.

  • The user asks "which unit depends on what?", "are there cycles?",

"what's the fan-in / fan-out?" against a Delphi codebase.

  • The user wants a visual artifact (Mermaid embed, SVG, DOT) summarizing

unit-level coupling.

Do not use this skill for non-Pascal codebases.

Inputs

The skill expects exactly one of:

  1. A .zip / .tar / .tar.gz archive of a Delphi project (preferred).
  2. A directory already containing .pas, .dpr, .dpk files.

If the user pastes raw Pascal source instead, persist it to one or more temporary .pas files first, then point --input at their parent directory.

Workflow

  1. Locate the input archive or directory in the working area.
  2. Run scripts/tool.py with --input pointing at it and --output

pointing at a fresh subfolder of the working area.

  1. Read the generated report.md and summarize findings to the user:

number of parsed units, top fan-in / fan-out, cycles, orphan units.

  1. Attach the produced artifacts (Mermaid, DOT, SVG when present, JSON,

report) to the response. Embed uses-graph.mmd inline in the answer so the user sees the diagram rendered.

Quick start

bash
python scripts/tool.py \
    --input  /path/to/project.zip \
    --output /path/to/out

Useful flags (full list in reference.md):

  • --scope {all,interface,implementation} — which uses sections to

consider. Default all.

  • --ignore-prefix LIST — drop edges whose target starts with one of these

comma-separated prefixes, case-insensitive. Default System,Winapi,Vcl,FMX,Data,Web,REST,IdGlobal. Pass "" to keep RTL/VCL.

  • --max-label N — truncate node labels in the Mermaid output (default 40).
  • --include-orphans — keep units that have no inbound and no outbound

edges in the graph.

Outputs (in --output)

FilePurpose
dependencies.jsonRaw graph: { unit: { defined_in, interface_uses, implementation_uses } }
uses-graph.mmdMermaid graph LR ready to embed in a markdown answer
uses-graph.dotGraphviz DOT source
uses-graph.svgSVG rendering — only when the dot binary is available on PATH
report.mdHuman-readable summary: counts, top hotspots, cycles, orphans

Notes

  • RTL / VCL / FMX targets are filtered by default to keep the diagram

readable. The user's own units are never filtered.

  • Cycle detection uses Tarjan's strongly connected components on the

directed graph (edge A -> B means A uses B). Self-loops are reported separately.

  • Pascal uses syntax has several edge cases (dotted names, in '<path>'

aliases, conditional defines, three comment styles). Read reference.md before changing the parser.

All versions