delphi-uses-graph

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, Graphviz DOT, optional SVG, JSON dependency dump, and markdown report.

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.

OpenAI Responses container note

This OpenAI-adapted bundle is intended to be registered through the OpenAI Skills API and attached to a Responses shell/container tool as a skill_reference. The analysis logic is vendor-neutral; the OpenAI-specific requirement is that the container can run Python and can read the uploaded Delphi project files.

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, 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.
2. A directory already containing .pas, .dpr, or .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 output folder.
3. Read the generated report.md and summarize parsed units, fan-in/fan-out, cycles, and orphan units.
4. Attach or surface the generated artifacts: Mermaid, DOT, SVG when present, JSON, and report. Embed uses-graph.mmd inline when the conversation surface supports Mermaid rendering.

Quick start

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

If the container exposes python3 instead of python, use python3 with the same arguments.

Useful flags, with full details 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

Files written in --output:

File	Purpose
dependencies.json	Raw graph: { unit: { defined_in, interface_uses, implementation_uses } }
uses-graph.mmd	Mermaid graph LR ready to embed in markdown
uses-graph.dot	Graphviz DOT source
uses-graph.svg	SVG rendering, only when the dot binary is available on PATH
report.md	Human-readable summary: counts, 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, and three comment styles. Read reference.md before changing the parser.