# Build Reliable Backend Services

Backend projects require consistent choices across APIs, databases, security, performance, and deployment. This skill provides structured workflows, checklists, commands, and FastAPI examples.

## Install

```bash
npx skillstore add zl2023github/backend-developer
```

## Metadata

- Status: approved
- Slug: zl2023github-backend-developer
- Skillstore revision: r2
- Version status: missing
- Tree hash: 1bbbd9fa9b3b59f8e1ddb0ade74988e39ec5f35192d2d27b6416b0f1a6d7bb56
- Author: zl2023github
- GitHub username: zl2023github
- License: MIT
- Repository: https://github.com/zl2023github/software-engineer-skills/tree/main/software-engineering/backend-developer
- Ref: 88a8e9a07f4c54ab105c1c41b6267c287146b07b
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network, filesystem
- Quality score: 69
- Public page: https://skillstore.pages.dev/skills/zl2023github-backend-developer
- Manifest: https://skillstore.pages.dev/api/skills/zl2023github-backend-developer/manifest

## Capabilities

- Clarifies language, framework, database, deployment, scale, and concurrency before design.
- Structures API routes, validation, business logic, persistence, errors, and tests.
- Reviews SQL plans, indexes, transactions, pagination, connection pools, and N\+1 queries.
- Applies security checks for validation, parameterized queries, authentication, CORS, rate limits, and secret handling.
- Guides performance diagnosis with tracing, logs, query analysis, caching, profiling, and load testing.
- Provides deployment checks for health probes, graceful shutdown, resource limits, backups, and observability.

## Use Cases

- Design a new API: Create an implementation plan with endpoints, validation, data models, indexes, errors, and tests.
- Review database performance: Analyze slow queries, execution plans, indexes, pagination, connection pools, and transaction boundaries.
- Prepare production deployment: Check probes, shutdown behavior, resources, logs, secrets, backups, and rollback readiness.

## Prompt Templates

### Plan a backend feature

```
Design a backend plan for [feature]. Ask about language, framework, database, deployment, data volume, and concurrency before proposing the architecture.
```

### Design an API and data model

```
Create endpoints and a data model for [workflow]. Include validation, authorization, error responses, indexes, transactions, pagination, and focused tests.
```

### Diagnose a production bottleneck

```
Analyze [symptoms] using [logs and metrics]. Rank likely causes, propose measurements, identify safe commands, and define rollback criteria before changes.
```

### Review service readiness

```
Review [service context] for security, performance, reliability, and deployment readiness. Produce prioritized findings, concrete fixes, verification steps, and unresolved risks.
```

## Limitations

- Does not inspect a repository unless the user provides access and context.
- Provides general guidance; framework and infrastructure details require project-specific adaptation.
- Command examples can change local or cluster state and require user review before execution.
- FastAPI snippets are illustrative and require production error handling, authentication, and tests.

## Best Practices

- Provide business requirements, expected traffic, data volume, framework, database, and deployment environment.
- Review every command and planned change against the target environment before execution.
- Verify recommendations with focused tests, query plans, metrics, security checks, and rollback steps.

## Anti Patterns

- Do not request implementation before defining requirements, scale, data ownership, and failure behavior.
- Do not run example commands against production without confirming scope, permissions, impact, and rollback.
- Do not expose raw exceptions, secrets, credentials, or sensitive records in logs and responses.

## Security Audit

- Audited at: 2026-07-24T02:13:07.299\+00:00
- Summary: All 33 static detections are false positives caused by Markdown formatting, local example URLs, safe device output, or ordinary technical prose. One semantic issue remains: the FastAPI example exposes raw exception details in client responses.

## Stats

- Views: 2
- Downloads: 5
- Favorites: 0
- Popularity score: 0