test▌
parcadei/continuous-claude-v3 · updated Apr 8, 2026
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Run comprehensive test suite with parallel execution.
/test - Testing Workflow
Run comprehensive test suite with parallel execution.
When to Use
- "Run all tests"
- "Test the feature"
- "Verify everything works"
- "Full test suite"
- Before releases or merges
- After major changes
Workflow Overview
┌─────────────┐ ┌───────────┐
│ diagnostics │ ──▶ │ arbiter │ ─┐
│ (type check)│ │ (unit) │ │
└─────────────┘ └───────────┘ │
├──▶ ┌─────────┐
┌───────────┐ │ │ atlas │
│ arbiter │ ─┘ │ (e2e) │
│ (integ) │ └─────────┘
└───────────┘
Pre-flight Parallel Sequential
(~1 second) fast tests slow tests
Agent Sequence
| # | Agent | Role | Execution |
|---|---|---|---|
| 1 | arbiter | Unit tests, type checks, linting | Parallel |
| 1 | arbiter | Integration tests | Parallel |
| 2 | atlas | E2E/acceptance tests | After 1 passes |
Why This Order?
- Fast feedback: Unit tests fail fast
- Parallel efficiency: No dependency between unit and integration
- E2E gating: Only run slow E2E tests if faster tests pass
Execution
Phase 0: Pre-flight Diagnostics (NEW)
Before running tests, check for type errors - they often cause test failures:
tldr diagnostics . --project --format text 2>/dev/null | grep "^E " | head -10
Why diagnostics first?
- Type check is instant (~1s), tests take longer
- Diagnostics show ROOT CAUSE, tests show symptoms
- "Expected int, got str" is clearer than "AttributeError at line 50"
- Catches errors in untested code paths
If errors found: Fix them BEFORE running tests. Type errors usually mean tests will fail anyway.
If clean: Proceed to Phase 1.
Phase 0.5: Change Impact (Optional)
For large test suites, find only affected tests:
tldr change-impact --session
# or for explicit files:
tldr change-impact src/changed_file.py
This returns which tests to run based on what changed. Skip this for small projects or when you want full coverage.
Phase 1: Parallel Tests
# Run both in parallel
Task(
subagent_type="arbiter",
prompt="""
Run unit tests for: [SCOPE]
Include:
- Unit tests
- Type checking
- Linting
Report: Pass/fail count, failures detail
""",
run_in_background=true
)
Task(
subagent_type="arbiter",
prompt="""
Run integration tests for: [SCOPE]
Include:
- Integration tests
- API tests
- Database tests
Report: Pass/fail count, failures detail
""",
run_in_background=true
)
# Wait for both
[Check TaskOutput for both]
Phase 2: E2E Tests (If Phase 1 Passes)
Task(
subagent_type="atlas",
prompt="""
Run E2E tests for: [SCOPE]
Include:
- End-to-end flows
- Acceptance tests
- UI tests if applicable
Report: Pass/fail count, screenshots on failure
"""
)
Test Scopes
Full Suite
User: /test
→ All unit + integration + E2E tests
Feature Scope
User: /test authentication
→ Only auth-related tests
Quick Check
User: /test --quick
→ Only unit tests (skip integration and E2E)
Example
User: /test the new payment feature
Claude: Starting /test workflow for payment feature...
Phase 0: Pre-flight diagnostics...
$ tldr diagnostics . --project --format text | grep "^E "
(no type errors found)
Phase 1: Running parallel tests...
┌─────────────────────────────────────────┐
│ arbiter: Running unit tests... │
│ arbiter: Running integration tests... │
└─────────────────────────────────────────┘
arbiter: ✅ 45/45 unit tests passing
arbiter: ✅ 12/12 integration tests passing
Phase 2: Running E2E tests...
atlas: ✅ 8/8 E2E tests passing
Test Summary:
┌─────────────┬─────────┬────────┐
│ Type │ Passed │ Failed │
├─────────────┼─────────┼────────┤
│ Unit │ 45 │ 0 │
│ Integration │ 12 │ 0 │
│ E2E │ 8 │ 0 │
├─────────────┼─────────┼────────┤
│ TOTAL │ 65 │ 0 │
└─────────────┴─────────┴────────┘
All tests passing! ✅
Example with Type Errors
User: /test
Claude: Starting /test workflow...
Phase 0: Pre-flight diagnostics...
$ tldr diagnostics . --project --format text | grep "^E "
E src/payment.py:45:12: Argument of type 'str' not assignable to 'int'
E src/refund.py:23:8: Return type 'None' not assignable to 'float'
Found 2 type errors. Fixing before running tests...
[Claude fixes the type errors]
Re-running diagnostics... clean.
Phase 1: Running parallel tests...
Failure Handling
If Phase 1 fails:
arbiter: ❌ 43/45 tests passing
2 failures:
- test_payment_validation: expected 'invalid' got 'valid'
- test_refund_calculation: off by $0.01
Stopping workflow. Fix failures before running E2E tests.
Flags
--quick: Unit tests only--no-e2e: Skip E2E tests--coverage: Include coverage report--watch: Re-run on file changes
How to use test 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 test
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches test from GitHub repository parcadei/continuous-claude-v3 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 test. Access the skill through slash commands (e.g., /test) 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
4.8★★★★★55 reviews- ★★★★★Pratham Ware· Dec 20, 2024
Solid pick for teams standardizing on skills: test is focused, and the summary matches what you get after install.
- ★★★★★Sofia Singh· Dec 20, 2024
test is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Arjun Zhang· Dec 16, 2024
test has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★James Shah· Dec 16, 2024
Keeps context tight: test is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Daniel Gupta· Dec 8, 2024
Registry listing for test matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Nikhil White· Dec 8, 2024
Solid pick for teams standardizing on skills: test is focused, and the summary matches what you get after install.
- ★★★★★Amelia Ndlovu· Nov 27, 2024
Useful defaults in test — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mateo Jain· Nov 11, 2024
test fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Carlos Thompson· Nov 7, 2024
We added test from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Arjun Liu· Oct 26, 2024
test fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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