testing▌
tursodatabase/turso · updated Apr 8, 2026
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SQL and Rust testing guide covering test types, execution, and writing patterns.
- ›Three primary test formats: .sqltest (preferred for SQL compatibility across backends), TCL .test (legacy, being phased out), and Rust integration tests for regression and complex scenarios
- ›Run tests via make test for the full suite, make -C testing/sqltests run-cli for SQL tests, or cargo test for Rust tests
- ›.sqltest format uses simple declarative syntax with @database , test blocks, and expect sections
Testing Guide
Test Types & When to Use
| Type | Location | Use Case |
|---|---|---|
.sqltest |
testing/sqltests/tests/ |
SQL compatibility. Preferred for new tests |
TCL .test |
testing/ |
Legacy SQL compat (being phased out) |
| Rust integration | tests/integration/ |
Regression tests, complex scenarios |
| Fuzz | tests/fuzz/ |
Complex features, edge case discovery |
Note: TCL tests are being phased out in favor of testing/sqltests. The .sqltest format allows the same test cases to run against multiple backends (CLI, Rust bindings, etc.).
Running Tests
# Main test suite (TCL compat, sqlite3 compat, Python wrappers)
make test
# Single TCL test
make test-single TEST=select.test
# SQL test runner
make -C testing/sqltests run-cli
# OR
cargo run -p test-runner -- run <test-file or directory>
# Rust unit/integration tests (full workspace)
cargo test
Writing Tests
.sqltest (Preferred)
@database :default:
test example-addition {
SELECT 1 + 1;
}
expect {
2
}
test example-multiple-rows {
SELECT id, name FROM users WHERE id < 3;
}
expect {
1|alice
2|bob
}
Location: testing/sqltests/tests/*.sqltest
You must start converting TCL tests with the convert command from the test runner (e.g cargo run -- convert <TCL_test_path> -o <out_dir>). It is not always accurate, but it will convert most of the tests. If some conversion emits a warning you will have to write by hand whatever is missing from it (e.g unroll a for each loop by hand). Then you need to verify the tests work by running them with make -C testing/sqltests run-rust, and adjust their output if something was wrong with the conversion. Also, we use harcoded databases in TCL, but with .sqltest we generate the database with a different seed, so you will probably need to change the expected test result to match the new database query output. Avoid changing the SQL statements from the test, just change the expected result
TCL
do_execsql_test_on_specific_db {:memory:} test-name {
SELECT 1 + 1;
} {2}
Location: testing/*.test
Rust Integration
// tests/integration/test_foo.rs
#[test]
fn test_something() {
let conn = Connection::open_in_memory().unwrap();
// ...
}
Key Rules
- Every functional change needs a test
- Test must fail without change, pass with it
- Prefer in-memory DBs:
:memory:(sqltest) or{:memory:}(TCL) - Don't invent new test formats. Follow existing patterns
- Write tests first when possible
Test Database Schema
testing/system/testing.db has users and products tables. See docs/testing.md for schema.
Logging During Tests
RUST_LOG=none,turso_core=trace make test
Output: testing/system/test.log. Warning: very verbose.
How to use testing on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add testing
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches testing from GitHub repository tursodatabase/turso and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate testing. Access the skill through slash commands (e.g., /testing) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★66 reviews- ★★★★★Amelia Haddad· Dec 28, 2024
testing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Pratham Ware· Dec 24, 2024
Registry listing for testing matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Arjun Martin· Dec 12, 2024
We added testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Alexander Rahman· Dec 8, 2024
testing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ishan Singh· Dec 8, 2024
testing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Alexander Agarwal· Dec 4, 2024
I recommend testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Arjun Torres· Nov 27, 2024
I recommend testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ira Smith· Nov 27, 2024
Registry listing for testing matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sofia Wang· Nov 23, 2024
testing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ren Verma· Nov 19, 2024
Registry listing for testing matched our evaluation — installs cleanly and behaves as described in the markdown.
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