backend-patterns

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Quality

31%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./docs/zh-TW/skills/backend-patterns/SKILL.md

Quality

Discovery

32%

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

The description identifies a reasonable domain and names specific technologies, which helps with targeting. However, it lacks concrete actions (listing categories rather than specific capabilities), misses a 'Use when...' clause entirely, and uses somewhat broad terminology that could overlap with other backend or full-stack skills.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about designing REST APIs, optimizing database queries, structuring Express middleware, or building Next.js API routes.'

Replace high-level categories with specific concrete actions, e.g., 'Designs RESTful and GraphQL APIs, optimizes SQL/NoSQL queries, structures Express middleware pipelines, and implements authentication patterns.'

Include more natural trigger terms users would say, such as 'REST', 'GraphQL', 'SQL', 'MongoDB', 'middleware', 'endpoints', 'server performance', and 'route handlers'.

Dimension	Reasoning	Score
Specificity	Names the domain (backend development) and some areas like 'API design', 'database optimization', and 'server-side best practices', but these are still fairly high-level categories rather than concrete actions. It doesn't list specific actions like 'design RESTful endpoints', 'write database queries', or 'configure middleware'.	2 / 3
Completeness	Describes 'what' at a high level (backend architecture, API design, etc.) but completely lacks any 'when' clause or explicit trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and since the 'what' is also somewhat vague, this scores a 1.	1 / 3
Trigger Term Quality	Includes some relevant keywords users might say like 'API design', 'database optimization', 'Node.js', 'Express', and 'Next.js API routes'. However, it misses common variations like 'REST', 'GraphQL', 'SQL', 'MongoDB', 'middleware', 'authentication', 'endpoints', or 'server' that users would naturally use.	2 / 3
Distinctiveness Conflict Risk	The mention of specific technologies (Node.js, Express, Next.js) helps narrow the scope, but 'backend architecture patterns' and 'server-side best practices' are broad enough to overlap with general coding skills, DevOps skills, or framework-specific skills.	2 / 3
	Total	7 / 12 Passed

Implementation

29%

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

This skill is essentially a comprehensive backend patterns cookbook dumped into a single file. While the code examples are high-quality and executable, the content is far too verbose for a skill file — most of these are standard patterns Claude already knows. It lacks any workflow guidance, decision framework, or progressive disclosure structure.

Suggestions

Drastically reduce content to project-specific conventions and decisions (e.g., 'We use Supabase RPC for transactions, repository pattern for data access') rather than teaching general patterns Claude already knows.

Add a workflow section that sequences when and how to apply these patterns (e.g., 'When adding a new API endpoint: 1. Define route, 2. Add repository method, 3. Add service logic, 4. Add auth middleware, 5. Test').

Split into a brief SKILL.md overview with links to separate reference files (e.g., AUTH_PATTERNS.md, CACHING.md, ERROR_HANDLING.md) for progressive disclosure.

Remove full implementations of universally known patterns (exponential backoff, rate limiter, structured logger) and replace with brief notes on project-specific conventions or configurations.

Dimension	Reasoning	Score
Conciseness	This is extremely verbose at ~400+ lines, covering many patterns (repository, service, middleware, caching, auth, rate limiting, queues, logging) with full implementations. Much of this is standard knowledge Claude already possesses — repository pattern, JWT verification, exponential backoff, rate limiting, structured logging are all well-known patterns that don't need full implementations spelled out. The skill reads like a textbook rather than a concise reference.	1 / 3
Actionability	The code examples are concrete, executable TypeScript with complete implementations. Each pattern includes copy-paste ready code with clear usage examples, specific to the Next.js/Supabase stack mentioned in the description.	3 / 3
Workflow Clarity	There is no workflow or sequencing — it's a catalog of isolated patterns with no guidance on when to apply them, in what order, or how they compose together. The transaction pattern involves destructive database operations but has no validation checkpoints. There's no decision framework for choosing between patterns.	1 / 3
Progressive Disclosure	This is a monolithic wall of code examples with no references to external files and no layered structure. All patterns are inlined at full detail with no overview/summary section pointing to deeper resources. Content that could be split into separate reference files (caching patterns, auth patterns, etc.) is all crammed into one document.	1 / 3
	Total	6 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (588 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: affaan-m/everything-claude-code
Commit: 5df943e

Reviewed: about 18 hours ago

Table of Contents

Discovery Implementation Validation

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