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Ln 56 Architecture Auditor

Community
levnikolaevich
ln-56-architecture-auditor

Audits implemented architecture boundaries, dependencies and ownership; not target design or plan review.

Overview

Publisherlevnikolaevich
Repositoryclaude-code-skills
Skill nameln-56-architecture-auditor
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 56 Architecture Auditor 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/quality-assurance-suite/skills/ln-56-architecture-auditor .claude/skills/ln-56-architecture-auditor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ln 56 Architecture Auditor 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 56 Architecture Auditor 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 56 Architecture Auditor 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 Auditor

Goal: Perform a read-only audit of the architecture the system actually executes. Evaluate whether structure, dependencies, contracts, and cross-component ownership fit current product needs without rewarding pattern names or speculative modernization. Judge where atomicity and resource ownership belong; leave local query, transaction, and data-resource correctness to a persistence-focused review.

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 toolUse it whenFallback
Physical and declared architectureNative file listing, manifests, build files, configuration, and architecture documentsEstablishing modules, packages, domains, layers, entrypoints, and deployment unitsTargeted repository map from known entrypoints
Symbols and dependency topologyLanguage server, compiler metadata, or host-native code intelligenceTracing imports, calls, implementations, routes, events, and cyclesNarrow search plus direct inspection of definitions and consumers
Runtime wiringRegistration code, dependency injection, routing, startup configuration, and safe runtime diagnosticsA component may exist but not be discoverable or connectedStatic trace with explicit uncertainty
Historical intentGit history, blame, and decision recordsA current exception or parallel mechanism may have a still-valid reasonCurrent behavior and documented constraints remain authoritative
Architectural fitnessCurrent official framework and platform documentationA finding depends on supported extension, lifecycle, configuration, or boundary behaviorPrimary-source web research; otherwise mark UNVERIFIED
Quantitative structureExisting dependency, cycle, complexity, or package-analysis commandsThe repository already defines reliable structural analysisReproducible static inventory and call-path evidence

Use diagrams only when they clarify a relationship that prose cannot. Do not generate a diagram as a substitute for evidence, and do not modify code or architecture documents during the audit.

Evidence Rules

  • Executable dependencies, runtime wiring, and public contracts outweigh intended diagrams or folder names.
  • A cycle or cross-layer call is a finding only when it creates a concrete change, ownership, testing, deployment, or failure cost.
  • Pattern compliance is not a goal by itself; evaluate fitness against product complexity, team workflow, and operational constraints.
  • Framework convention and generated wiring require framework-aware verification before being labeled leakage or dead code.
  • Modernization is justified only by a present defect or measurable simplification, not novelty.
  • Explicit repository boundary rules define intended constraints; documentation explains them; inference from folder names is low-confidence evidence and must not create a violation by itself.
  • A prior audit baseline separates new, resolved, and accepted debt. It does not make an active correctness or security risk disappear.
  • Shared system-design baseline, current-state, target-design, decision, diagram, and migration artifacts are optional intent evidence. Their absence is not a defect by itself, and their presence never outranks executable behavior for the implemented state.

Checklist

1. Discover the Actual Architecture

  • Read repository instructions, architecture documents, manifests, entrypoints, deployment definitions, and configuration ownership rules.
  • Discover shared architecture artifacts by repository convention, distinguish a system-design baseline from a prior audit baseline, and classify each as current, proposed, accepted, superseded, stale, contradictory, or UNKNOWN; do not require any particular artifact path.
  • Map packages, modules, domains, layers, processes, data stores, queues, external systems, and public interfaces in scope.
  • Record ownership and independent build, deploy, scale, and failure boundaries; do not infer a service boundary from a directory or process name alone.
  • Identify the dominant organizing model and any competing models: layer-first, domain-first, service boundaries, plugin boundaries, or framework conventions.
  • Trace representative critical flows from entrypoint through orchestration, domain behavior, persistence or integration, and observable outcome.
  • Compare documented current state, target state, accepted decisions, and active migration phase with executable structure; record drift and authority conflicts without assuming documentation describes what actually runs.
  • Inspect Git state so current work and unrelated user changes are not misclassified as established architecture.
  • Keep the audit read-only and disclose any permitted diagnostic caches or generated analysis artifacts.

2. Audit Pattern Fitness and Ownership

  • Identify major patterns from behavior and assess problem fit, completeness, consistency, and evidenced maintenance cost; avoid invented numeric scores.
  • Check whether abstractions remove real volatility or merely move straightforward code behind interfaces, factories, registries, or generic layers.
  • Check layer direction, domain ownership, orchestration depth, side-effect boundaries, and whether policy remains separated from infrastructure detail.
  • Trace where cross-component transactions, sessions, connections, streams, processes, subscriptions, and background work are owned; report boundary ambiguity without duplicating local lifecycle or transaction-correctness analysis.
  • For each state-changing critical flow, identify the atomicity owner and how partial failure is prevented, retried idempotently, or compensated across stores and messages.
  • Check read-named or pure-looking interfaces for hidden writes, broad side effects, network calls, or lifecycle ownership that violates their contract.
  • Find parallel architectural mechanisms, partially completed migrations, compatibility paths with no consumer, and extension points with no credible variation.
  • Check whether failure handling and retries sit at the layer that owns the operation rather than being duplicated or swallowed across layers.

3. Audit Contracts and Dependencies

  • Inspect public API, service, event, command, and persistence boundaries for stable input/output models plus explicit error, nullability, idempotency, and compatibility contracts.
  • Check whether shared entity or framework types, missing boundary models, boolean modes, excessive parameters, unstable serialization, or naming drift create coupling or contract ambiguity; do not demand DTOs where a shared model is an intentional stable contract.
  • Build module or package dependency direction using resolved internal edges; account for aliases, re-exports, generated code, reflection, registries, plugins, and runtime loading before declaring an edge absent.
  • Apply configured forbidden/allowed dependency rules first; if rules are only inferred, report the inferred model and confidence instead of presenting it as policy.
  • Identify forbidden imports, cycles, unstable dependency direction, excessive fan-in/fan-out, and isolated islands; use structural metrics to locate candidates, then apply the consequence check below.
  • Trace cycle and coupling findings to concrete effects on change radius, initialization, testing, deployment, ownership, or failure propagation.
  • Check that producers and consumers agree on event names, schemas, versions, delivery semantics, ordering, and registration.
  • Check physical structure for domain cohesion, framework placement, junk drawers, duplicate module roots, orphan packages, and files whose location hides ownership.
  • Check configuration boundaries for typed settings, composition-root ownership, precedence and override semantics, startup validation, scattered environment reads, secret ownership, and leakage into domain behavior.
  • Verify runtime discovery: routes, handlers, jobs, commands, plugins, middleware, serializers, and dependency bindings must be registered and reachable.

4. Evaluate Evolution and Alternatives

  • Identify current architecture pain using repository evidence: repeated change sets, fragile tests, broad blast radius, duplicate mechanisms, release coupling, or incident-prone ownership.
  • If a system-design baseline exists, verify its source and freshness, then compare confirmed constraints with actual behavior.
  • If a prior audit baseline exists, compare new, resolved, and retained findings; continue to report accepted or retained risks when their impact remains material.
  • Research external pattern or framework behavior only when it can confirm a capability, limitation, lifecycle rule, or supported simplification.
  • Compare the current shape with the simplest credible alternative, including migration risk, compatibility, rollback, team impact, and operational cost.
  • Prefer incremental boundary repair when a rewrite or new pattern would create more transitional complexity than it removes.
  • Reject recommendations that require speculative scale, unsupported future variants, or replacement of working conventions without a demonstrated defect.
  • Include a migration sequence only when the recommendation cannot be applied safely as one bounded change.

5. Validate Findings and Report

  • Verify structural findings through at least one dependency path, call path, registration path, public contract, or reproducible analysis result.
  • Filter generated code, framework conventions, deliberate adapters, test-only architecture, and documented exceptions before confirming a violation.
  • Apply the materiality gate: require concrete correctness, security, ownership, deployment, change amplification, or recurring maintenance impact at evidenced scale. Reject taste, theoretical purity, generic practice, hypothetical scale, and reasonable alternatives; require the outcome or constraint, not a preferred implementation.
  • External correction evidence: Ground external corrections in version-matched official contracts, using primary engineering sources for unresolved tradeoffs. Cite the supported mechanism; local evidence suffices for local defects.
  • Link each accepted boundary finding to the violated driver or contract and the smallest independently verifiable remediation scope; distinguish architectural proposals from accepted decisions.
  • Classify findings as P0-P3 based on correctness, security, change amplification, deployment coupling, and recurring maintenance cost.
  • Order recommendations by prerequisite and risk reduction, separating immediate correctness fixes from optional evolution.
  • Use BLOCKED when required runtime wiring, boundary evidence, or an authoritative contract cannot be verified without a credible fallback; use FAIL for an evidenced unresolved correctness or security boundary defect, unsafe ownership ambiguity, or P0/P1 structural risk; use CONCERNS only for material non-blocking change amplification, and PASS only when no evidenced architecture defect creates material cost or risk.

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: Actual modules, boundaries, wiring, dependencies, configuration, and critical flows; distinguish current, target, transition, and drift. Findings need priority, affected boundary, evidence, consequence at current scale, unacceptable tradeoff, migration risk, and smallest safe next step; allow equivalent target shapes. Order evolution by prerequisites and preserve accepted exceptions.

Frequently asked questions

What does the Ln 56 Architecture Auditor AI skill do?

Audits implemented architecture boundaries, dependencies and ownership; not target design or plan review.

Why use Ln 56 Architecture Auditor on TypingMind?

Because you install it once and use it with any model. Ln 56 Architecture Auditor 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 56 Architecture Auditor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/levnikolaevich/claude-code-skills/tree/master/plugins/quality-assurance-suite/skills/ln-56-architecture-auditor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ln 56 Architecture Auditor?

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 56 Architecture Auditor?

As many as you like. As long as a model supports skills, you can use Ln 56 Architecture Auditor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ln 56 Architecture Auditor 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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