differential-fuzzer▌
tursodatabase/turso · updated Apr 8, 2026
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Property-based fuzzer that compares Turso against SQLite to catch SQL correctness bugs.
- ›Generates random SQL statements and schemas, then executes them on both Turso and SQLite to detect mismatches in row sets, error handling, or schema state
- ›Supports deterministic reproduction via seed-based runs, configurable statement/table/column counts, and verbose output for debugging
- ›Includes continuous loop mode for extended fuzzing campaigns and Docker runner for CI with configurable timeout
Differential Fuzzer
Always load Debugging skill for reference
The differential fuzzer compares Turso results against SQLite for generated SQL statements to find correctness bugs.
Location
testing/differential-oracle/fuzzer/
Running the Fuzzer
Single Run
# Basic run (100 statements, random seed)
cargo run --bin differential_fuzzer
# With specific seed for reproducibility
cargo run --bin differential_fuzzer -- --seed 12345
# More statements with verbose output
cargo run --bin differential_fuzzer -- -n 1000 --verbose
# Keep database files after run (for debugging)
cargo run --bin differential_fuzzer -- --seed 12345 --keep-files
# All options
cargo run --bin differential_fuzzer -- \
--seed <SEED> # Deterministic seed
-n <NUM> # Number of statements (default: 100)
-t <NUM> # Number of tables (default: 2)
-c <NUM> # Columns per table (default: 5)
--verbose # Print each SQL statement
--keep-files # Persist .db files to disk
Continuous Fuzzing (Loop Mode)
# Run forever with random seeds
cargo run --bin differential_fuzzer -- loop
# Run 50 iterations
cargo run --bin differential_fuzzer -- loop 50
Docker Runner (CI/Production)
# Build and run from repo root
docker build -f testing/differential-oracle/fuzzer/docker-runner/Dockerfile -t fuzzer .
docker run -e GITHUB_TOKEN=xxx -e SLACK_WEBHOOK_URL=xxx fuzzer
Environment variables for docker-runner:
TIME_LIMIT_MINUTES- Total runtime (default: 1440 = 24h)PER_RUN_TIMEOUT_SECONDS- Per-run timeout (default: 1200 = 20min)NUM_STATEMENTS- Statements per run (default: 1000)LOG_TO_STDOUT- Print fuzzer output (default: false)GITHUB_TOKEN- For auto-filing issuesSLACK_WEBHOOK_URL- For notifications
Output Files
All output goes to simulator-output/ directory:
| File | Description |
|---|---|
test.sql |
All executed SQL statements. Failed statements prefixed with -- FAILED:, errors with -- ERROR: |
schema.json |
Database schema at end of run (or at failure) |
test.db |
Turso database file (only with --keep-files) |
test-sqlite.db |
SQLite database file (only with --keep-files) |
Reproducing Errors
Always follow these steps
-
Find the seed in the error output:
INFO: Starting differential_fuzzer with config: SimConfig { seed: 12345, ... } -
Re-run with that seed:
cargo run --bin differential_fuzzer -- --seed 12345 --verbose --keep-files -
Check output files:
simulator-output/test.sql- Find the failing statement (look for-- FAILED:)simulator-output/schema.json- Check table structure at failure time
-
Create a minimal reproducer
- Create reproducer in
.sqltestor in.rsalways load Debugging skill for reference
- Create reproducer in
-
Compare behavior manually: If needed try to compare the behaviour and produce a report in the end. Always write to a tmp file first with Edit tool to test the sql and then pass it to the binaries.
# Run failing SQL against SQLite sqlite3 :memory: < simulator-output/test.sql # Run against tursodb CLI tursodb :memory: < simulator-output/test.sql
Understanding Failures
Oracle Failure Types
- Row set mismatch - Turso returned different rows than SQLite
- Turso errored but SQLite succeeded - Turso rejected valid SQL
- SQLite errored but Turso succeeded - Turso accepted invalid SQL
- Schema mismatch - Tables/columns differ after DDL
Warning (non-fatal)
- Unordered LIMIT mismatch - LIMIT without ORDER BY may return different valid rows
Key Source Files
| File | Purpose |
|---|---|
main.rs |
CLI parsing, entry point |
runner.rs |
Main simulation loop, executes statements on both DBs |
oracle.rs |
Compares Turso vs SQLite results |
schema.rs |
Introspects schema from both databases |
memory/ |
In-memory IO for deterministic simulation |
Tracing
Set RUST_LOG for more detailed output:
RUST_LOG=debug cargo run --bin differential_fuzzer -- --seed 12345
How to use differential-fuzzer 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 differential-fuzzer
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches differential-fuzzer 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 differential-fuzzer. Access the skill through slash commands (e.g., /differential-fuzzer) 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▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★44 reviews- ★★★★★Anika Martin· Dec 4, 2024
We added differential-fuzzer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Dev Wang· Dec 4, 2024
differential-fuzzer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Liam Jain· Nov 23, 2024
Keeps context tight: differential-fuzzer is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Liam Martinez· Oct 14, 2024
differential-fuzzer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Oshnikdeep· Sep 21, 2024
We added differential-fuzzer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Li Liu· Sep 21, 2024
Solid pick for teams standardizing on skills: differential-fuzzer is focused, and the summary matches what you get after install.
- ★★★★★Min Chawla· Sep 21, 2024
differential-fuzzer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Daniel Jackson· Sep 5, 2024
Useful defaults in differential-fuzzer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakshi Patil· Sep 1, 2024
Registry listing for differential-fuzzer matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Li Wang· Aug 24, 2024
I recommend differential-fuzzer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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