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umlforge_reverse_engineer

Read-only

Analyze any codebase from a GitHub URL or pasted code to generate UML class, sequence, and state diagrams with architectural insights.

Instructions

Analyse an existing codebase and produce UML class, sequence, and state diagrams.

USE THIS WHEN:

  • You have a GitHub URL and want to understand what the code does

  • You want to audit a codebase for architectural problems

  • You need diagrams of code that already exists (your own or a public repo)

  • You want an Architectural Intelligence Report on any codebase

NOT FOR:

  • Designing a new system from scratch → use umlforge_stakeholder_arch

  • Updating diagrams after a sprint → use umlforge_living_docs

  • Documenting database schema → use umlforge_erd_schema

  • Mapping how services call each other → use umlforge_api_sequence

Produces:

  • Class diagram: entities, attributes, relationships, multiplicities

  • Sequence diagram: primary execution flow or dominant use case

  • State diagram: entity lifecycle (if stateful entities are detected)

  • Architectural smell flags: god classes, circular deps, anemic models

  • (report_mode=True) Architectural Intelligence Report: system overview, key findings, modernisation roadmap, health scores (A–F)

Provide EITHER github_url OR codebase — not both.

Args: github_url: Public GitHub URL. Accepted formats: github.com/owner/repo github.com/owner/repo/tree/branch/path/to/dir github.com/owner/repo/blob/branch/path/to/file.py codebase: Paste code directly when you have files in context or the repo is private. max_nodes: Max classes/components per diagram (default 20). report_mode: True → also produce an Architectural Intelligence Report. Pro/Team/Enterprise only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codebaseNo
max_nodesNo
github_urlNo
report_modeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and destructiveHint, but the description adds significant context about outputs (diagrams, report, architectural smells) and the mutual exclusion of github_url and codebase. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (USE THIS WHEN, NOT FOR, Produces, Args). It is front-loaded with the main purpose. Slightly verbose but each sentence adds value; condensing the NOT FOR list slightly could improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 parameters, multiple output types), the description covers all usage constraints, output details, and parameter documentation. It compensates for the missing output schema description by explaining what each output contains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description provides detailed semantics for each parameter (e.g., accepted GitHub URL formats, default value for max_nodes, and the effect of report_mode). This fully compensates for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Analyse' and resource 'existing codebase' producing UML diagrams. It distinguishes from siblings via explicit 'NOT FOR' section naming alternatives like umlforge_stakeholder_arch and umlforge_living_docs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a 'USE THIS WHEN' list for appropriate contexts and a 'NOT FOR' list with explicit sibling tool names, offering clear guidance on when to use this tool vs alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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