naiba-openai-engineers

# Engineers Assistant

This skill provides **20+ professional prompts** tailored for Engineers professionals.

## Available Categories

### Research & benchmarking

**Evaluate cloud providers for migration**

```
I'm an infrastructure engineer evaluating cloud migration options. Context: We're moving from on-prem to the cloud for a fintech backend. Output: Compare AWS, GCP, and Azure for scalability, pricing, compliance, and developer tooling. Include citations.
```

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**Research frameworks for real-time apps**

```
I'm building a real-time collaboration tool. Context: We need low-latency and scalability. Output: Compare top frameworks (e.g., SignalR, Socket.io, WebRTC) with use cases, pros/cons, and current usage by other SaaS companies. Include sources.
```

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**Benchmark observability tools**

```
Benchmark the top observability tools. Context: We want to move from basic logging to full-stack monitoring. Output: Create a comparison table of features, pricing, integrations for Datadog, New Relic, Prometheus, and OpenTelemetry. Include sources.
```

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**Analyze AI/ML trends in logistics**

```
I'm researching AI/ML adoption in logistics systems. Context: Our company is considering integrating predictive routing. Output: A 5-paragraph summary on current trends, vendors, and implementation patterns. Include citations and links.
```

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**Investigate compliance best practices**

```
Research best practices for GDPR/CCPA compliance so we can help kick off discussions with our legal team. Context: Our app stores sensitive user data in the EU and US. Output: A compliance checklist with citations, sorted by regulation. Include links to documentation and regulations.
```

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### Technical reviews & documentation

**Review system design doc**

```
I've drafted a technical design document for [insert project or feature]. Review it for clarity, architectural soundness, and completeness. Highlight any missing considerations or questions reviewers may raise.
```

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**Document internal API behavior**

```
I need to document how this internal API works for other developers. Here's the relevant code, schema, and usage examples: [insert materials]. Create clear documentation including endpoints, input/output formats, and expected behavior.
```

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**Draft runbook for on-call engineers**

```
I need to create a runbook for on-call engineers supporting [insert system]. Draft one that includes sections for system overview, common alerts, diagnostic steps, and escalation procedures.
```

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**Draft onboarding guide for new hires**

```
I need to write an onboarding guide for new engineers joining [insert team]. Create a draft with sections for required tools, access setup, codebase overview, and first tasks. Make it suitable for self-service onboarding.
```

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**Write JIRA ticket from spec**

```
Based on this engineering spec for [insert task or feature], write a JIRA ticket that includes the problem statement, context, goals, acceptance criteria, and technical notes for implementation.
```

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### Debugging & optimization

**Debug failing system in production**

```
A system in production is intermittently failing, and we're struggling to isolate the root cause. Based on the following logs, metrics, and recent changes: [insert context], help identify the most likely causes and suggest next steps for mitigation.
```

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**Analyze performance bottlenecks**

```
Our service is experiencing latency and degraded performance during peak usage. Here are metrics, logs, and relevant traces: [insert context]. Help identify the bottlenecks and recommend specific optimizations.
```

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**Analyze a data pipeline failure**

```
A critical data pipeline failed in yesterday's run. Here are the logs, data volume trends, and error outputs: [insert context]. Analyze what likely went wrong and provide recommendations to prevent recurrence.
```

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**Suggest observability improvements**

```
We currently use [insert tools] for monitoring [insert service]. Review our observability setup and suggest improvements across metrics, logging, alerting, and dashboards to improve issue detection and debugging.
```

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**Brainstorm edge cases for testing**

```
We're preparing test cases for [insert feature/system]. Brainstorm potential edge cases and failure scenarios that may not be covered by standard testing, including unusual user inputs, system state changes, and concurrency issues.
```

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### Data analysis & reporting

**Identify trends in product usage logs**

```
Analyze this CSV of product usage logs. Context: We want to identify usage trends over time and across user segments. Output: Summary stats + line or bar charts highlighting key trends.
```

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**Visualize system error rates over time**

```
Plot error rates over time from this dataset. Context: It contains application logs from the last month. Output: A time-series chart with callouts for error spikes and a short interpretation.
```

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**Analyze performance test results**

```
Analyze this set of performance test results. Context: It compares two versions of our backend service. Output: Side-by-side comparison charts + text summary of improvements or regressions.
```

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**Prioritize bugs based on impact**

```
Analyze this bug report dataset. Context: Each row includes severity, frequency, and affected users. Output: A prioritized list of top bugs with charts showing frequency vs. severity.
```

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**Summarize feedback from user surveys**

```
Summarize this user feedback CSV. Context: It includes ratings and open text responses from a recent survey. Output: Key themes, sentiment scores, and charts showing distribution of ratings.
```

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