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backend-development

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.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/backend-development/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%

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

Well-structured with excellent progressive disclosure and a useful decision matrix, but the body stays at the overview/decision level: it lacks executable examples and validation checkpoints, and pads conciseness with unsourced statistic claims.

Suggestions

Add at least one minimal executable snippet per major area (e.g. a parameterized-query example, a Dockerfile, a CI workflow) to lift actionability toward copy-paste-ready.

Insert explicit validation/checkpoint gates into the checklists (e.g. 'migrate → run migration tests → only then deploy') to satisfy the feedback-loop requirement for risky ops.

Replace or source the unsourced percentage claims in 'Key Best Practices'; otherwise move them to a reference file so the overview stays lean.

DimensionReasoningScore

Conciseness

The body is lean and uses bullets, a matrix, and checklists with no concept-explanation fluff, but the 'Key Best Practices (2025)' section is padded with unsourced statistics ('98% SQL injection reduction', 'Vitest 50% faster', '83% migrations fail') that read as marketing claims rather than instruction, so it is mostly efficient rather than fully tight.

2 / 3

Actionability

Concrete decision guidance exists (decision matrix, step checklists like 'Choose style → Design schema → Validate input → Add auth'), but there is no executable code or commands and the checklists are high-level flows, falling short of the copy-paste-ready score-3 anchor without being merely vague.

2 / 3

Workflow Clarity

Sequences are present (API, database, security, testing, deployment checklists) but lack explicit validation checkpoints or feedback loops; given risky operations like DB migrations and deployment, the rubric's guidance caps workflow clarity at 2 when validation gates are missing.

2 / 3

Progressive Disclosure

A concise overview points to 11 well-organized one-level-deep references grouped under clear category headings ('Core Technologies', 'Security & Authentication', etc.), each confirmed as a real file in ./references/, matching the clear-overview-with-well-signaled-references anchor rather than the inline-wall-of-text score-2 example.

3 / 3

Total

9

/

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.

A strong, complete description with explicit 'Use when' triggers and concrete capabilities, weakened only by its breadth, which raises overlap risk with adjacent coding skills. Voice is correctly third person.

Suggestions

Narrow the scope or add a distinguishing qualifier (e.g. 'server-side/API-layer backend') to reduce overlap with fullstack or database-specific skills.

Trim the parenthetical technology enumerations, which pad length without adding trigger value; keep only the terms users would naturally say.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('implementing authentication', 'optimizing database queries', 'setting up CI/CD pipelines', 'building microservices') tied to named technologies, matching the multiple-specific-actions anchor rather than the single-domain score-2 example.

3 / 3

Completeness

Explicitly answers both what ('Build robust backend systems with...') and when ('Use when designing APIs, implementing authentication...'), matching the score-3 anchor exactly rather than the what-only score-2 example.

3 / 3

Trigger Term Quality

Natural trigger phrases users would say appear explicitly ('designing APIs', 'implementing authentication', 'optimizing database queries', 'setting up CI/CD pipelines', 'handling security vulnerabilities') in third person, giving good coverage; the long parenthetical tech-name lists add jargon but do not displace the natural triggers.

3 / 3

Distinctiveness Conflict Risk

The trigger set is fairly distinct (APIs, auth, DB queries, CI/CD, security, microservices) but 'production-ready backend systems' is broad and could overlap with frontend/fullstack or database-specific skills, so it is only somewhat specific rather than a clear niche.

2 / 3

Total

11

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
mrgoonie/claudekit-skills
Reviewed

Table of Contents

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