/diagnose-clickhouse-errors
Diagnose ClickHouse runtime query failures when the user wants database-level cause and fix guidance from an error or numeric error code, not source-code root cause analysis.
$ npx -y skills add FrankChen021/datastoria --skill diagnose-clickhouse-errors --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/diagnose-clickhouse-errors
Context preview
The summary Claude sees to decide when to auto-load this skill.
Diagnose ClickHouse runtime query failures when the user wants database-level cause and fix guidance from an error or numeric error code, not source-code root cause analysis.
SKILL.md
diagnose-clickhouse-errors.SKILL.mdname: diagnose-clickhouse-errors
description: Diagnose ClickHouse runtime query failures when the user wants database-level cause and fix guidance from an error or numeric error code, not source-code root cause analysis.
metadata:
author: DataStoria
When Not To Use
Do not use this skill when the user's primary goal is:
- investigating application or repository source code
- tracing where failing SQL was constructed in code
- finding code paths that produced the ClickHouse error
In those cases, prefer `source-code-inspection`. Do not start this skill's error-code intake flow unless the user is asking for database-level diagnosis.
Workflow
1. Determine whether the user is asking for database-level diagnosis or source-code investigation. If the primary goal is source-code investigation or file-cited code analysis, stop and prefer `source-code-inspection`. 2. Extract the numeric ClickHouse error code from the conversation or error text (e.g. `Code: 60`). 3. If no numeric error code is detected and the user is asking for database-level diagnosis, call `ask_user_question` with exactly one question. Do NOT reply with natural-language text before the tool call.
- `header`: `Please provide a ClickHouse error code for diagnosis`
- `options`: `[ { "id": "error_code", "label": "error code", "input": "text" } ]`
- Treat the returned `value` as the numeric error code and continue.
4. Load `references/<code>.md` with `skill_resource` (e.g. `references/60.md`) and follow its workflow. 5. If the orchestrator provides database context facts, use them when they materially change the cause or fix. 6. If `skill_resource` returns nothing, use your ClickHouse knowledge to provide a best-effort response.
Response format
- **Section 1 (Cause)** — One short sentence explaining why the error occurred.
- **Section 2 (Fix)** — Bullet list of concrete steps.
- **Section 3 (Example)** — A single fenced SQL block with the corrected query; omit if not applicable.
Heading rules:
- Default (English): use headings `## Cause`, `## Fix`, and optional `## Example`.
- If a response language is specified by system policy or user message (`Response language (BCP-47): …`), localize the heading text to that language while keeping the same 3-section structure.
- Keep SQL, codes, and identifiers as-is.
Keep answers brief and action-first. Do not repeat the raw error verbatim. Do not add extra headings.
Read more
name: diagnose-clickhouse-errors description: Diagnose ClickHouse runtime query failures when the user wants database-level cause and fix guidance from an error or numeric error code, not source-code root cause analysis. metadata: author: DataStoria
When Not To Use
Do not use this skill when the user's primary goal is:
- investigating application or repository source code
- tracing where failing SQL was constructed in code
- finding code paths that produced the ClickHouse error
In those cases, prefer `source-code-inspection`. Do not start this skill's error-code intake flow unless the user is asking for database-level diagnosis.
Workflow
1. Determine whether the user is asking for database-level diagnosis or source-code investigation. If the primary goal is source-code investigation or file-cited code analysis, stop and prefer `source-code-inspection`. 2. Extract the numeric ClickHouse error code from the conversation or error text (e.g. `Code: 60`). 3. If no numeric error code is detected and the user is asking for database-level diagnosis, call `ask_user_question` with exactly one question. Do NOT reply with natural-language text before the tool call.
- `header`: `Please provide a ClickHouse error code for diagnosis`
- `options`: `[ { "id": "error_code", "label": "error code", "input": "text" } ]`
- Treat the returned `value` as the numeric error code and continue.
4. Load `references/<code>.md` with `skill_resource` (e.g. `references/60.md`) and follow its workflow. 5. If the orchestrator provides database context facts, use them when they materially change the cause or fix. 6. If `skill_resource` returns nothing, use your ClickHouse knowledge to provide a best-effort response.
Response format
- **Section 1 (Cause)** — One short sentence explaining why the error occurred.
- **Section 2 (Fix)** — Bullet list of concrete steps.
- **Section 3 (Example)** — A single fenced SQL block with the corrected query; omit if not applicable.
Heading rules:
- Default (English): use headings `## Cause`, `## Fix`, and optional `## Example`.
- If a response language is specified by system policy or user message (`Response language (BCP-47): …`), localize the heading text to that language while keeping the same 3-section structure.
- Keep SQL, codes, and identifiers as-is.
Keep answers brief and action-first. Do not repeat the raw error verbatim. Do not add extra headings.
The AI-native ClickHouse console for your cluster diagnostics, query generation, evidence-based optimization, intelligent visualization.
Repo: FrankChen021/datastoria
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Open skill

