What do I need to use SQL Query Explainer?

The SQL; The intent in plain words; Optional but transformative (optional).

Is SQL Query Explainer free to use?

Yes — run it free in the browser playground (no API key needed for the sponsored trial, or bring any provider key), or install it into Claude Code, Cursor, ChatGPT and more via npx pm-claude-skills. MIT-licensed and open source.

SQL Query Explainer

Q: How do I know the SQL Query Explainer output is good?

The skill verifies itself against its own quality checks: Plain English explanation avoids SQL jargon; Optimisation suggestions include before/after SQL; Written queries include inline comments; Output shape is described (columns, row grain, ordering).

🔵 Stable🕐 updated 2026-07-08 ✅ 4.3/5 🔷 SkillSpec L3 pm-data

Explains, optimises, writes, and documents SQL queries. Use when asked to explain a SQL query, optimise slow SQL, translate SQL to plain English for non-technical stakeholders, write a query from a natural language description, or produce query documentation. Produces plain-English explanations, annotated optimised queries, or a data dictionary covering output shape, assumptions, and known limitations. Works across PostgreSQL, MySQL, BigQuery, Snowflake, and standard SQL.

▶ Run it free — no key needed 📝 Grade your existing draft View SKILL.md ↗

🗣 Say this to your agent

“Explain this SQL query: [paste query]”“Optimise this slow query: [paste query]”“Write a SQL query that [natural language description]”“Document this query for my non-technical stakeholders”“Why is this query returning unexpected results?”

What to give it

▸The SQL — (Explain/Optimise/Document modes) — the actual query, ideally with the dialect named (Postgres, BigQuery, Snowflake, MySQL…); dialect changes both semantics and the optimisation advice.

▸The intent in plain words — (Write mode) — what question the data should answer, plus table/column names if known. Without a schema, assumptions get stated, never silently invented.

▸Optional but transformative (optional) — `EXPLAIN`/`EXPLAIN ANALYZE` output and rough table sizes — turns generic advice into advice about *your* query plan.

✅ The bar it holds itself to

Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.

✓Plain English explanation avoids SQL jargon

✓Optimisation suggestions include before/after SQL

✓Written queries include inline comments

✓Output shape is described (columns, row grain, ordering)

✓Dialect-specific syntax is flagged when non-standard

⚠️ What it refuses to do

Restating the SQL in pseudo-code instead of explaining what it *does* and *returns*

Optimisation advice with no before/after query, or no reason the new one is faster

Ignoring the dialect (writing Postgres-only syntax for a MySQL user)

"Looks fine" with no read on correctness, performance, or row grain

Rewriting the query from scratch instead of explaining/optimising the user's

Install

npx pm-claude-skills add --agent claude   # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcp

Start with

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💬 Discussion

SQL Query Explainer is one of 1174 open-source professional AI agent skills — all SkillSpec L3. Try them all in the browser · ⭐ Star on GitHub · Browse the full catalog