AI‑Assisted SQL Development for Cli Tools

AI‑assisted SQL development for CLI tools thrives when you give models clear objectives, audience context, and constraints. This article packages practical prompt patterns you can reuse and adapt so results improve with every iteration. Lead with the outcome you want, define tone and format, and include short examples. Ask for two alternatives and a brief rationale.

How to use these prompts: Paste the prompt, then ask follow‑ups like “What assumptions did you make?”, “Offer stronger rewrites in different tones,” and “Highlight risks or edge cases to review.” This tight loop compounds quality quickly.

Starter Prompts

  • Design a SQL module for , including tests and docstrings.
  • Explain to a junior dev and provide a commented SQL example.
  • Create a script to parse CSV and output JSON with schema validation.

Advanced Variations

  • Refactor legacy SQL code for readability and complexity with before/after.
  • Generate a performance profile and propose three micro‑optimizations.
  • Author a README with install steps, examples, and gotchas.

Refinement & QA

  • Write unit tests covering edge cases and failure modes.
  • Add CI/CD notes and a minimal Dockerfile for reproducible builds.
  • Produce a code review checklist and an issue template for contributors.

Frameworks & Templates

  • SPEC: | INPUTS: | OUTPUTS: | CONSTRAINTS:
  • DOC: | | |
  • TEST PLAN: | |

Examples & Inputs

  • Build a SQL CLI that fetches an API and writes a CSV report.
  • Create a SQL microservice that validates webhooks and logs events.
  • Write SQL code to migrate a database column with zero downtime.

Evaluation Rubric

  • Correctness and robustness under edge cases
  • Readability and maintainability (naming, structure)
  • Performance characteristics (complexity, memory)
  • Completeness of tests and docs

Iteration Checkpoints

  • Run linter/formatter and static analysis
  • Benchmark critical path with sample data
  • Security review for input handling

Metrics & KPIs

  • Test coverage percentage
  • p95 latency or runtime
  • Defects found in code review

Pro tip: Save best outputs as mini‑templates labeled with audience, tone, format, and success metric. Stack them into a personal prompt system that covers ideation → drafting → editing → QA → conversion.