backend-architect

Designs scalable backend architectures, models relational database schemas, builds REST/GraphQL/gRPC APIs, configures cloud infrastructure, and implements microservices with security and observability built in. Use when asked to design a backend system, create or version an API, write a database schema or migration, set up microservices, plan cloud deployment architecture, implement authentication/authorization, configure caching or message queues, or optimize server-side performance. Covers PostgreSQL, Redis, RabbitMQ, Docker, Kubernetes, and Infrastructure as Code.

Quality

84%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

77%

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

This is a strong, well-structured backend architecture skill with excellent workflow clarity and highly actionable code examples. Its main weakness is that the deliverable templates section adds significant length that could be better handled through progressive disclosure into separate reference files. The core conventions and workflows are concise and valuable, providing exactly the kind of opinionated, concrete guidance that makes a skill effective.

Suggestions

Move the Architecture Deliverable Templates section into a separate TEMPLATES.md file and reference it from the main skill with a one-line link per template type.

Trim the Core Conventions section slightly—some bullet sub-points (e.g., 'secrets injected via environment, never committed') are repeated in the Decision Checklist and templates.

Dimension	Reasoning	Score
Conciseness	The skill is mostly efficient and avoids explaining basic concepts Claude already knows, but the architecture deliverable templates section is quite lengthy and could be trimmed or moved to a separate reference file. The inline templates add bulk that competes with conversation context.	2 / 3
Actionability	Provides fully executable SQL schemas, working JavaScript API endpoint code, concrete migration workflows with specific steps, and a decision checklist with verifiable items. The code examples are copy-paste ready and include security middleware, rate limiting, and proper error handling.	3 / 3
Workflow Clarity	All three workflows (Schema Change, New Service, API Versioning) are clearly sequenced with explicit validation checkpoints. The Schema Change workflow includes dry-run validation, explain-plan capture, and a monitor-then-rollback feedback loop with specific thresholds. The decision checklist adds a final verification gate.	3 / 3
Progressive Disclosure	The content is well-structured with clear sections and headers, but the deliverable templates are inlined rather than referenced from separate files. For a skill of this length (~120 lines of substantive content), the templates could be split into referenced files to keep the main skill leaner and improve navigation.	2 / 3
	Total	10 / 12 Passed

Description

92%

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

This is a strong, well-crafted description that excels in specificity and completeness, with concrete actions, explicit 'Use when' triggers, and named technologies. Its main weakness is the very broad scope, which increases the risk of overlapping with more specialized skills in any of its sub-domains. The third-person voice is used correctly throughout.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'designs scalable backend architectures', 'models relational database schemas', 'builds REST/GraphQL/gRPC APIs', 'configures cloud infrastructure', 'implements microservices with security and observability'. Very comprehensive and action-oriented.	3 / 3
Completeness	Clearly answers both 'what' (designs architectures, models schemas, builds APIs, configures infrastructure, implements microservices) and 'when' with an explicit 'Use when...' clause listing eight distinct trigger scenarios. Also includes a technology coverage statement.	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'backend system', 'API', 'database schema', 'migration', 'microservices', 'cloud deployment', 'authentication/authorization', 'caching', 'message queues', 'server-side performance', plus specific technologies like 'PostgreSQL', 'Redis', 'RabbitMQ', 'Docker', 'Kubernetes'. These are all terms users would naturally use.	3 / 3
Distinctiveness Conflict Risk	While the description is detailed, the scope is very broad—covering databases, APIs, cloud infrastructure, microservices, caching, auth, and message queues. This breadth means it could overlap with more specialized skills for database design, API development, cloud infrastructure, or authentication individually. A user asking about 'PostgreSQL schema' could trigger this or a dedicated database skill.	2 / 3
	Total	11 / 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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: OpenRoster-ai/awesome-agents
Commit: 010799b

Reviewed: 3 months ago

Table of Contents

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