Ln 25 Architecture Diagram Builder logo

Ln 25 Architecture Diagram Builder

Community
levnikolaevich
ln-25-architecture-diagram-builder

Creates evidence-backed current or target architecture diagrams; not UI design.

Overview

Publisherlevnikolaevich
Repositoryclaude-code-skills
Skill nameln-25-architecture-diagram-builder
Stars
565
Forks
84
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by levnikolaevich on GitHub. Read the source before you install it.

Installation

Install the Ln 25 Architecture Diagram Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/levnikolaevich/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/plugins/architecture-suite/skills/ln-25-architecture-diagram-builder .claude/skills/ln-25-architecture-diagram-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ln 25 Architecture Diagram Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ln 25 Architecture Diagram Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ln 25 Architecture Diagram Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Architecture Diagram Builder

Goal: Create the smallest set of understandable, evidence-backed diagrams needed to communicate current or proposed architecture. Change only approved architecture documentation; do not invent relationships, perform visual product design, replace prose evidence, audit fitness, or edit implementation.

Execution contract: The checklist defines completion. Track each item internally as PENDING, PROVEN with evidence, CLEARED with evidence its condition is absent, or UNPROVEN with a gap; reading, delegation, or tool failure is not proof. Reconcile after each section. Before returning, resolve all PENDING, count only PROVEN and CLEARED, and apply verdict and approval rules to every gap. Preserve intent, scope, and existing authorization. Continue authorized work; ask only for consequential unresolved choices or required external approval. Scale depth to material risk without skipping checks. Preserve dependency and safety order; otherwise choose an appropriate verification method. Accept equivalent user or repository evidence; no other skill, named artifact, or complete lifecycle is required. Preserve source requirement and decision IDs. Bind reused evidence to relevant source versions, dirty changes, configuration, and environment; invalidate only affected claims. On continuation, reconcile task, authorization, current state, and unresolved evidence. For long work, return a compact continuation record or update an already authorized artifact; read-only skills do not persist it. Distinguish artifact readiness, verified behavior, and external-action authority. Prepare authorized work before required approval. If blocked by an instruction, cite its exact source and unresolved boundary; do not invent approval gates from caution.

Tool Routing

NeedPreferred capabilityFallback
Architecture evidenceRepository files, runtime wiring, IaC, contracts, and approved artifactsUser-provided model with UNVERIFIED labels
Relationship tracingLanguage intelligence, dependency tools, and focused searchDirect inspection of producers, consumers, and registrations
Diagram formatExisting repository convention and rendererMermaid in Markdown, then plain ASCII
Syntax verificationRepository renderer, parser, or previewManual fence, identifier, and relationship inspection
Document mutationMinimal patch to approved diagram artifactsReturn BLOCKED if path or evidence boundary is unsafe

Diagrams communicate a model; executable behavior remains authoritative for current state. Keep current, target, and transition views visibly distinct.

Artifact Rules

  • Reuse an existing diagram convention or use docs/architecture/diagrams/<view>.md.
  • Prefer Markdown with Mermaid for text-reviewable source; use ASCII when Mermaid is unsupported.
  • For static structure, choose the context, container, or component level that answers the requested question; do not create prerequisite overview diagrams when existing context suffices.
  • Keep diagram source reviewable in version control.
  • Split views when one diagram needs multiple unrelated stories.
  • Never use color as the only carrier of meaning.
  • Use stable element identifiers and concise display labels so revisions produce reviewable diffs.
  • Keep detailed evidence beside the diagram rather than crowding nodes and relationships.
  • Preserve an understandable existing notation; introduce a new notation only when it answers the audience question better.

Checklist

1. Establish the Diagram Contract

  • Resolve audience, question, current or target state, scope, approved destination, and required notation.
  • Read repository instructions, relevant architecture artifacts, and existing diagram conventions.
  • Select the minimum useful view or views; reject diagrams that add no relationship clarity.
  • Define the evidence boundary and label user-supplied or proposed elements separately.
  • Keep the run read-only except for approved architecture diagram documentation.

2. Build the Architecture Model

  • Identify relevant people, systems, applications/data stores (C4 containers when using C4), components, queues, and external dependencies; distinguish logical containers from OS/container-runtime deployment units.
  • Record responsibility, type, technology when decision-relevant, owner when known, and current/target status for each element.
  • Resolve relationship direction, label, protocol or data, synchronicity, and trust or network boundary where relevant.
  • Trace runtime discovery and registration before including current-state routes, handlers, jobs, plugins, or consumers.
  • Mark uncertain elements or relationships UNKNOWN rather than completing the picture aesthetically.

3. Select and Draw Views

  • Create a system-context view when readers need system scope and external actors.
  • Create a container or deployment view for responsibilities, deployability, stores, or operational topology; include nodes, regions, networks, scaling, and failover when relevant to the audience question.
  • Create a component view only for a complex area whose internal boundaries change understanding.
  • Create sequence or dynamic views for critical success, failure, retry, timeout, recovery, or migration interactions.
  • Create data-flow or trust-boundary views when security, privacy, residency, or system-of-record questions require them.
  • Avoid mixing abstraction levels in one view unless the exception is explicit and necessary.

4. Make the Diagram Self-Describing

  • Add title, diagram type, scope, current/target marker, intended audience, and observation or proposal date.
  • Add a legend for shapes, colors, line styles, abbreviations, and uncertainty markers.
  • Label every relationship with intent or data; avoid generic arrows and unexplained acronyms.
  • Keep names consistent with code, contracts, and shared architecture documents.
  • Add compact evidence notes or links sufficient to trace current-state claims.

5. Verify and Report

  • Validate syntax with the repository renderer or perform a complete manual syntax inspection.
  • Inspect rendered readability when a preview is available and split overloaded views rather than shrinking labels. Without a renderer, record visual readability as UNPROVEN; manual syntax inspection is not render proof.
  • Verify current-state elements and relationships against implementation evidence, and target-state elements against the declared proposal or explicitly labelled assumptions.
  • Bind each view to current or proposed architecture and its authoritative source; expose contradictions rather than resolving them silently in a diagram.
  • Use READY when diagrams are valid, scoped, evidenced, and readable at the requested fidelity; use INCONCLUSIVE for material unknown relationships or missing required render evidence; use BLOCKED when scope, evidence, format, or destination prevents a trustworthy diagram.

Self-Check

  • Reconcile before returning. Check item-level evidence, requirement coverage, contradictions, scope, verdict, and applicable cleanup. Correct the report or authorized artifacts. Reuse valid evidence; do not automatically rescan the repository or rerun successful commands. Repeat checks only for relevant changes, failures, or unresolved evidence. Disclose remaining gaps.

Output Contract

Report in the user's language, in this order; retain all five fields and state each fact once. Small results may use one line per field; omit empty tables and do not copy linked artifacts:

  1. Result: Skill-specific verdict and supported outcome.
  2. Scope: Reviewed/changed scope, exclusions, baseline, and material assumptions.
  3. Evidence: Skill-specific fields below; distinguish facts, inferences, and unverified claims. Link artifacts; use tables when useful.
  4. Verification: Checks/results, unavailable evidence, and applicable cleanup/external state.
  5. Completion: Checklist: X/Y complete; Incomplete: None or each UNPROVEN item's reason, outcome impact, and exact next action; residual risks and required decisions.

Skill-specific evidence: Artifact paths; each view’s current/target state, audience question, and evidence basis. Report syntax/render verification and current-state relationship checks, unknown relationships, and rendering limits that affect interpretation.

Frequently asked questions

What does the Ln 25 Architecture Diagram Builder AI skill do?

Creates evidence-backed current or target architecture diagrams; not UI design.

Why use Ln 25 Architecture Diagram Builder on TypingMind?

Because you install it once and use it with any model. Ln 25 Architecture Diagram Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ln 25 Architecture Diagram Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/levnikolaevich/claude-code-skills/tree/master/plugins/architecture-suite/skills/ln-25-architecture-diagram-builder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ln 25 Architecture Diagram Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ln 25 Architecture Diagram Builder?

As many as you like. As long as a model supports skills, you can use Ln 25 Architecture Diagram Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ln 25 Architecture Diagram Builder AI skill free?

Yes. It is published on GitHub by levnikolaevich under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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