AgentSkillsCN

dataql-auto-issue

当 DataQL 出现错误时，自动创建 GitHub 问题，并进行重复性校验。当 DataQL 命令失败或产生意外错误时，可使用此技能。

SKILL.md
--- frontmatter
name: dataql-auto-issue
description: Automatically create GitHub issues when DataQL errors occur, with duplicate validation. Use when DataQL commands fail or produce unexpected errors.
tools:
  - Bash

DataQL Auto-Issue Reporter

You have the ability to automatically create GitHub issues when DataQL commands fail. This ensures errors are tracked and helps improve the tool.

When to Create Issues

Create an issue when:

  • •DataQL command fails with an error
  • •Unexpected behavior occurs
  • •A bug is reproducible
  • •The error message suggests a code problem (not user error)

Do NOT create issues for:

  • •User errors (wrong file path, invalid SQL syntax user typed)
  • •Missing dependencies on user's system
  • •Network/permission issues
  • •Expected behavior that user misunderstands

Duplicate Validation (REQUIRED)

ALWAYS check for existing issues before creating a new one:

Step 1: Search for similar issues

bash
gh issue list --repo adrianolaselva/dataql --state all --search "<error keywords>" --limit 20

Step 2: Check if duplicate exists

Look for issues with:

  • •Similar error messages
  • •Same component/feature affected
  • •Similar reproduction steps

Step 3: If duplicate found

  • •Add a comment to the existing issue with additional context
  • •Do NOT create a new issue
bash
gh issue comment <issue_number> --repo adrianolaselva/dataql --body "Additional occurrence reported:
- Context: <context>
- Error: <error>
- Version: $(dataql --version 2>/dev/null || echo 'unknown')"

Step 4: If no duplicate found

  • •Create a new issue with full details

Issue Creation

Get System Information

bash
# Get DataQL version
dataql --version 2>/dev/null || echo "version unknown"

# Get OS info
uname -a

# Get Go version (if relevant)
go version 2>/dev/null || echo "go not found"

Create Issue

bash
gh issue create --repo adrianolaselva/dataql \
  --title "[Bug] <short description>" \
  --label "bug,auto-reported" \
  --body "$(cat <<'EOF'
## Description
<Brief description of the issue>

## Error Message
<exact error message> ```

Steps to Reproduce

  1. •<step 1>
  2. •<step 2>
  3. •<step 3>

Expected Behavior

<what should have happened>

Actual Behavior

<what actually happened>

Environment

  • •DataQL Version: <version>
  • •OS: <os info>
  • •Input File Type: <csv/json/etc>

Command Executed

bash
<the exact command that failed>

Additional Context

<any relevant context>

This issue was auto-reported by Claude Code EOF )"

code

## Labels

Use appropriate labels:
- `bug` - For errors and unexpected behavior
- `auto-reported` - Indicates automated reporting
- `file-handler` - Issues with CSV, JSON, Parquet handlers
- `database` - Issues with PostgreSQL, MySQL, MongoDB connectors
- `storage` - Issues with DuckDB storage layer
- `mcp` - Issues with MCP server integration
- `repl` - Issues with interactive mode
- `export` - Issues with data export functionality

## Common Error Patterns

### File Handler Errors
```bash
# Search pattern
gh issue list --repo adrianolaselva/dataql --state all --search "file handler csv json parquet"

Database Connection Errors

bash
# Search pattern
gh issue list --repo adrianolaselva/dataql --state all --search "database connection postgres mysql mongodb"

Storage/DuckDB Errors

bash
# Search pattern
gh issue list --repo adrianolaselva/dataql --state all --search "duckdb storage insert"

Type Inference Errors

bash
# Search pattern
gh issue list --repo adrianolaselva/dataql --state all --search "type inference column mismatch"

Example Workflow

Error Occurs

code
$ dataql run -f data.csv -q "SELECT * FROM data"
Error: failed to infer column types: unexpected nil value in row 150

Check for Duplicates

bash
gh issue list --repo adrianolaselva/dataql --state all --search "infer column types nil value"

No duplicate found - Create Issue

bash
gh issue create --repo adrianolaselva/dataql \
  --title "[Bug] Type inference fails with nil value in middle of data" \
  --label "bug,auto-reported,storage" \
  --body "## Description
Type inference fails when a CSV file contains nil/empty values after row 100.

## Error Message
\`\`\`
Error: failed to infer column types: unexpected nil value in row 150
\`\`\`

## Steps to Reproduce
1. Create a CSV with 200 rows
2. Leave some cells empty in rows 150+
3. Run: dataql run -f data.csv -q \"SELECT * FROM data\"

## Expected Behavior
DataQL should handle nil values gracefully, using NULL in the database.

## Actual Behavior
Command fails with type inference error.

## Environment
- DataQL Version: v1.0.0
- OS: Linux 6.6.87.2-microsoft-standard-WSL2
- Input File Type: CSV

## Command Executed
\`\`\`bash
dataql run -f data.csv -q \"SELECT * FROM data\"
\`\`\`

---
*This issue was auto-reported by Claude Code*"

Important Notes

  1. •Always validate duplicates first - This prevents issue spam
  2. •Include version information - Essential for debugging
  3. •Provide exact error messages - Copy verbatim, don't paraphrase
  4. •Include reproduction steps - Be specific and minimal
  5. •Use appropriate labels - Helps maintainers triage
  6. •Respect user privacy - Don't include sensitive data in issues

Authentication

Ensure gh CLI is authenticated:

bash
gh auth status

If not authenticated, prompt the user to authenticate:

bash
gh auth login