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sql-expert

Expert system for generating, validating, and optimizing ClickHouse SQL. Use this when the user needs data, queries, or analysis.

Quellinformationen

Repository
FrankChen021/datastoria
Letzte Quellaktivität
16. März 2026 um 13:16
Erkannte Sprache von SKILL.md
Englisch
Sterne
327
Forks
18

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
sql-expert
description
Expert system for generating, validating, and optimizing ClickHouse SQL. Use this when the user needs data, queries, or analysis.
metadata
{"author":"System","disable-slash-command":true}
> ## 🚨 CRITICAL RULE: MANDATORY VALIDATION > You **MUST** call `validate_sql(sql)` for **every** new query you generate. > **Context Note**: Historical validation steps are pruned to save tokens, but this does NOT excuse you from validating new queries in the current turn. Always validate before executing. # 1. Schema Discovery & Context - **Missing Schema**: If you do not have the table schema, you MUST use `get_tables` and `explore_schema` first. - *Optimization*: If the user already mentioned exact field names, pass them in the `columns` argument of `explore_schema` instead of loading the full table schema. - **Exact Identifier Rule**: Treat exact identifier-like tokens from the user question as candidate columns on the first schema lookup. This especially applies to ClickHouse metric names such as `ProfileEvent_*`, `CurrentMetric_*`, and flattened event columns on `system.*` tables. - **Missing Columns**: If you don't see the expected column, retry `explore_schema` with a narrower `columns` list based on the user-mentioned identifier or the closest confirmed column names. - **Schema Fidelity**: Only use columns that are confirmed to exist in the table schema from `explore_schema`. Do not assume standard columns exist if they are not in the tool output. - **User Context**: If the user asks about "my data", use `WHERE user = '<clickHouseUser>'`. - **System Tables**: For queries on `system.*` tables (e.g., `system.query_log`, `system.parts`, `system.merges`), defer to the `clickhouse-system-queries` skill - it contains table-specific patterns, predicates, and resource metrics that this skill does not cover. For `system.query_log`, do not generate SQL until `references/system-query-log.md` has been loaded via `skill_resource`, and do not call `search_query_log` for chart/time-series requests. # 2. Syntax Rules (The Grammar) - **Tables**: ALWAYS use fully qualified names (e.g., `database.table`). - **Semicolons**: NEVER include a trailing semicolon (`;`). - **Enums**: Use exact string literals for Enum columns. - **Safety**: ALWAYS use `LIMIT` for data exploration queries. # 3. Optimization Rules (Best Practices) - **Time filters**: Always filter by the partition key (usually `event_date` or `timestamp`) first. Use **bounded time windows** (e.g., last 24h, 7 days) unless the user asks for all history. - **Primary Keys (CRITICAL)**: ClickHouse indexes are sparse. You **MUST** filter on the **leading column** of the Primary Key if you filter on any secondary column. - *Bad*: `WHERE event_time > now() - 1h` (If PK is `event_date, event_time`, this scans everything). - *Good*: `WHERE event_date >= toDate(now() - 1h) AND event_time > now() - 1h` (Uses index, handles midnight crossover). - **Approximation**: Use `uniq()` instead of `uniqExact()` unless precision is explicitly requested. - **Joins**: Put the **smaller table on the RIGHT**. Use `GLOBAL IN` only for distributed queries. # 4. Execution Workflow 1. **Generate**: Create the SQL following the rules above. 2. **Validate (MANDATORY)**: Call `validate_sql(sql)`. - *If invalid*: Read the error, fix the SQL, and retry (max 3 attempts). 3. **Decide Action**: - *Visualization*: IF the user wants a chart, DO NOT execute. Pass the SQL to the visualization skill logic. - *Data*: IF the user wants answers (lists, counts), call `execute_sql(sql)`. - *Code Only*: IF the user asks to "write SQL", just output the code block.
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