component-common-domain-detection

Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic duplicated?", "find common code between services", "what can be consolidated?", "detect shared domain logic", or analyzing component overlap before refactoring. Do NOT use for code-level duplication detection (use linters) or dependency analysis (use coupling-analysis).

Quality

65%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./packages/skills-catalog/skills/(architecture)/component-common-domain-detection/SKILL.md

Quality

Content

48%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body delivers a well-sequenced five-phase methodology with executable detection code and useful checklists, but it is significantly overlong and padded, inlining material that belongs in bundle files and leaving the crucial input-acquisition step (how to build the component/import model and compute CA from a real repo) unspecified.

Suggestions

Cut the redundant "How to Use" quick-start and "Usage Examples" sections, which restate the Step-by-Step Process verbatim, and trim the Core Concepts and Node/Java directory-layout sections that explain what Claude can infer — this could halve the body.

Move Implementation Notes, Detection Strategies, and Fitness Functions code into a references/ bundle file, keeping SKILL.md as a concise overview with clearly signaled one-level-deep pointers.

Add concrete guidance for acquiring the inputs the analysis depends on: how to enumerate components and their imports from an actual codebase, and how statement counts and afferent-coupling (CA) metrics are computed.

Dimension	Reasoning	Score
Conciseness	The ~600-line body restates the same five steps three times across "How to Use", "Usage Examples", and "Step-by-Step Process", explains domain-vs-infrastructure concepts Claude can infer, and includes Node.js/Java directory layouts that are padded filler — matching the "several unnecessary explanations or padded sections" anchor rather than the mostly-efficient level 3.	2 / 5
Actionability	Includes genuinely executable JavaScript (groupByLeafNode, findSharedClasses, fitness functions) and concrete example outputs, but never specifies how to obtain the required inputs — the component model with .namespace/.imports, statement counts, and CA (afferent coupling) metrics — from a real codebase, which is a missing key detail keeping it below the mostly-executable level 4.	3 / 5
Workflow Clarity	A clear five-phase sequence with an Analysis Checklist and coupling-impact guardrails ("Don't consolidate without analyzing coupling impact") gives most checkpoints, but there is no explicit validate-fix-retry feedback loop, so it does not reach the level-5 anchor. The operations are analytical rather than destructive/batch, so no cap applies.	4 / 5
Progressive Disclosure	No bundle files exist; everything is inlined in one ~600-line SKILL.md, with Implementation Notes, Fitness Functions code, and full output-format templates that clearly belong in separate reference files. Clear section headers provide navigable structure, fitting the level-3 anchor ("content that should be separate is inline") rather than the minimal-structure level 2.	3 / 5
	Total	12 / 20 Passed

Description

82%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description with an explicit what, explicit when using natural quoted trigger phrases, and effective negative boundaries. The only gaps are modest: it under-sells the skill's full capability set and could add a few more synonym trigger phrases.

Dimension	Reasoning	Score
Specificity	Names the domain ("duplicate business logic spread across multiple components") and two concrete actions ("Finds", "suggests consolidation"), matching the anchor for 1-2 concrete actions but not the comprehensive several-action coverage of level 4 — capabilities the body delivers like shared-class detection and coupling analysis are absent from the description.	3 / 5
Completeness	Explicitly answers both what ("Finds duplicate business logic spread across multiple components and suggests consolidation") and when ("Use when asking..." with concrete trigger phrases), plus negative triggers, matching the level-5 anchor exactly.	5 / 5
Trigger Term Quality	Five quoted natural phrases ("where is this logic duplicated?", "find common code between services", "what can be consolidated?", "detect shared domain logic", "analyzing component overlap before refactoring") give good keyword coverage, but common variations like "DRY", "deduplicate", or "extract shared logic" are missing, so it falls short of the comprehensive synonym coverage of level 5.	4 / 5
Distinctiveness Conflict Risk	Clear niche (domain-level duplication across components) with explicit negative triggers routing code-level duplication to linters and dependency analysis to coupling-analysis, minimizing conflict risk with neighboring skills.	5 / 5
	Total	17 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (607 lines); consider splitting into references/ and linking	Warning

	Total	15 / 16 Passed

Repository: tech-leads-club/agent-skills
Path: packages/skills-catalog/skills/(architecture)/component-common-domain-detection/SKILL.md
Commit: 120b676

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.