backend-engineer

Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

Install with Tessl CLI

npx tessl i github:siviter-xyz/dot-agent --skill backend-engineer

What are skills?

Review — 82%

Does it follow best practices?

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Learn more

Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Discovery

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, comprehensive skill description that clearly articulates capabilities and provides explicit trigger conditions. The main weakness is its breadth—covering so many backend domains (APIs, databases, DevOps, security, authentication) that it could conflict with more specialized skills in any of these individual areas.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions and technologies: 'designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices.' Also enumerates specific technologies like Node.js, Python, PostgreSQL, Docker, Kubernetes.	3 / 3
Completeness	Clearly answers both what ('Build robust backend systems with modern technologies...') AND when ('Use when designing APIs, implementing authentication, optimizing database queries...'). The explicit 'Use when...' clause provides clear trigger guidance.	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'APIs', 'authentication', 'database queries', 'CI/CD pipelines', 'security vulnerabilities', 'microservices', 'backend systems', plus specific technology names like 'Node.js', 'FastAPI', 'PostgreSQL', 'Docker', 'Kubernetes'.	3 / 3
Distinctiveness Conflict Risk	While backend-focused, the extremely broad scope (covering APIs, databases, DevOps, security, authentication, microservices) could overlap with more specialized skills for individual domains like 'database optimization', 'Docker/Kubernetes', 'API design', or 'security auditing'.	2 / 3
	Total	11 / 12 Passed

Implementation

72%

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

This skill excels at being a concise, well-organized navigation hub for backend development topics. The decision matrices and checklists provide good high-level guidance. However, it lacks concrete executable code examples and explicit validation checkpoints in workflows, making it more of a reference index than an actionable implementation guide.

Suggestions

Add at least one concrete, executable code example for a common task (e.g., a FastAPI endpoint with authentication, or a PostgreSQL query with proper parameterization)

Enhance implementation checklists with explicit validation steps (e.g., 'Database: Design schema → **Validate with test data** → Create indexes → **Verify query plans** → ...')

Include a brief error recovery pattern for at least one critical workflow (e.g., what to do if a migration fails mid-deployment)

Dimension	Reasoning	Score
Conciseness	Extremely lean and efficient. Uses tables, bullet points, and brief phrases. No unnecessary explanations of concepts Claude already knows. Every section delivers actionable information without padding.	3 / 3
Actionability	Provides good decision matrices and checklists, but lacks concrete executable code examples. The checklists are helpful but remain at the conceptual level (e.g., 'Add auth' rather than showing how). References external files for implementation details.	2 / 3
Workflow Clarity	Implementation checklists provide clear sequences, but lack explicit validation checkpoints and feedback loops. For operations like database migrations or deployments, there's no 'validate before proceeding' or error recovery guidance.	2 / 3
Progressive Disclosure	Excellent structure with clear overview and well-organized one-level-deep references. The 'Reference Navigation' section clearly signals where to find detailed information, organized by domain (Core, Security, Performance, Quality).	3 / 3
	Total	10 / 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

Reviewed: 11 days ago

Table of Contents

Discovery Implementation Validation

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