Runs a sequenced monolith-to-modular pipeline that sizes and inventories components, finds shared domain duplication, addresses flattening and hierarchy issues, analyzes coupling, then groups components into candidate domain-aligned units, with optional embedded DDD strategic analysis for bounded contexts. Use when asking how to split a monolith, size components before extraction, find duplicated domain logic, clean up module hierarchy, measure coupling between modules, or group components into services. Do NOT use for phased extraction roadmaps or prioritization without the prior analysis steps (use decomposition-planning-roadmap after this pipeline), end-to-end legacy migration strategy writeups (use legacy-migration-planner), pure infrastructure capacity sizing, or when you only need DDD without the structural pipeline (install domain-analysis standalone).
npx skills add https://github.com/tech-leads-club/agent-skills --skill modular-decomposition
This skill runs the Patterns 1–5 analysis pipeline before service extraction. Each pattern is plain markdown under references/; load the file for that step and execute it against the user’s codebase.
If the user only wants extraction order, phases, or migration roadmap after analysis exists, use decomposition-planning-roadmap instead. If they need a full legacy migration plan (strangler fig, research, multi-stack), use legacy-migration-planner as well or instead of this skill when that is the primary ask.
references/pattern-NN-*.md file and follow its instructions. Use the optional *-quick-reference.md for the same number when a short checklist is enough.references/domain-analysis.md before or alongside Pattern 5. Optionally open references/domain-analysis-quick-reference.md or references/domain-analysis-examples.md for condensed rules or illustrations.Example 1 — Full pipeline
User: "We're going to split this monolith—run the full decomposition analysis (Patterns 1–5)."
Agent: Execute patterns 1→5 in order, loading each references/pattern-NN-*.md, preserving outputs between steps, then summarize cross-cutting recommendations.
Example 2 — Coupling after inventory
User: "We already have a rough module list—focus on coupling (Pattern 4) and then domain grouping (Pattern 5)."
Agent: If no prior inventory exists in the thread, either run Pattern 1 briefly or derive an explicit module list from the repo before 4 and 5. State any assumptions.
Example 3 — DDD before grouping
User: "Map bounded contexts and language, then group components into domains."
Agent: Read references/domain-analysis.md (and optional quick reference/examples) in parallel with or immediately before Pattern 5; align Pattern 5 groupings with linguistic boundaries where evidence supports it.
references/domain-analysis.md before or alongside Pattern 5 (see Bounded contexts below).| Step | Pattern | Primary reference |
| ---- | ---------------------------------- | ---------------------------------------------------------------------------------------------------------- |
| 1 | Identify and size components | references/pattern-01-identify-and-size.md (optional: pattern-01-identify-and-size-quick-reference.md) |
| 2 | Common domain detection | references/pattern-02-common-domain.md (optional: pattern-02-common-domain-quick-reference.md) |
| 3 | Flattening / hierarchy | references/pattern-03-flattening.md (optional: pattern-03-flattening-quick-reference.md) |
| 4 | Coupling analysis | references/pattern-04-coupling.md |
| 5 | Domain identification and grouping | references/pattern-05-domain-grouping.md (optional: pattern-05-domain-grouping-quick-reference.md) |
Pattern 6 (_create domain services / extraction_) is not duplicated here. After Pattern 5, switch to decomposition-planning-roadmap for phased extraction order, milestones, and migration-style planning. For full legacy migration strategy (strangler-fig, cross-stack rewrites, research-heavy plans), optionally use legacy-migration-planner in addition.
references/domain-analysis.md, with optional domain-analysis-quick-reference.md and domain-analysis-examples.md. Use it when you need to validate or refine boundaries against business language, not only folder structure.Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off. This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation. Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility
Automate Cloudinary media management including folder organization, upload presets, asset lookup, transformations, and usage monitoring through natural language commands
You are a workflow automation expert specializing in creating efficient CI/CD pipelines, GitHub Actions workflows, and automated development processes. Design automation that reduces manual work, improves consistency, and accelerates delivery while maintaining quality and security.
Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.
Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.
Build and operate reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. Use for DNAnexus data transfers, dxapp.json development, execution monitoring, workflow import, and project automation.
Search across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical details. When an agent needs to: (1) Find or search for information about systems, terminology, processes, deployment, authentication, infrastructure, architecture, or technical concepts, (2) Search internal documentation, knowledge base, company docs, or our docs, (3) Explain what something is, how it works, or look up information, or (4) Synthesize information from multiple sources. Searches in parallel and provides cited answers.
Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.
Take tech-leads-club/modular-decomposition from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.