---
name: tdd-workflows-tdd-green-a88b59ca1480
description: "Implement the minimal code needed to make failing tests pass in the TDD green phase."
risk: unknown
source: community
date_added: "2026-02-27"
---

# Green Phase: Simple function
def product_list(request):
    products = Product.objects.all()
    return JsonResponse({'products': list(products.values())})

# Refactor: Class-based view
class ProductListView(View):
    def get(self, request):
        products = Product.objects.all()
        return JsonResponse({'products': list(products.values())})

# Refactor: Generic view
class ProductListView(ListView):
    model = Product
    context_object_name = 'products'
```

### Express Patterns

**Inline → Middleware → Service Layer:**
```javascript
// Green Phase: Inline logic
app.post('/api/users', (req, res) => {
  const user = { id: Date.now(), ...req.body };
  users.push(user);
  res.json(user);
});

// Refactor: Extract middleware
app.post('/api/users', validateUser, (req, res) => {
  const user = userService.create(req.body);
  res.json(user);
});

// Refactor: Full layering
app.post('/api/users',
  validateUser,
  asyncHandler(userController.create)
);
```

## Use this skill when

- Moving from red to green in a TDD cycle
- Implementing minimal behavior to satisfy tests
- You want to keep implementation intentionally simple

## Do not use this skill when

- You are refactoring for design or performance
- Tests are already passing and you need new requirements
- You need a full architectural redesign

## Instructions

1. Review failing tests and identify the smallest fix.
2. Implement the minimal change to pass the next test.
3. Run tests after each change to confirm progress.
4. Record shortcuts or debt for the refactor phase.

## Safety

- Avoid bypassing tests to make them pass.
- Keep changes scoped to the failing behavior only.

## Resources

- `resources/implementation-playbook.md` for detailed patterns and examples.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.


---
Source attribution: Sukumar-Elley
Original contribution (preserved): https://github.com/Sukumar-Elley/antigravity-awesome-skills/blob/5925731a273265928e78954df711358072c8de5b/plugins/antigravity-awesome-skills-claude/skills/tdd-workflows-tdd-green/SKILL.md
License: MIT + CC-BY-4.0
License information: https://creativecommons.org/licenses/by/4.0/
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Antigravity User

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


Creative Commons Attribution 4.0 International (CC BY 4.0)

This file clarifies the license for original non-code repository content.

- Original code and tooling remain licensed under the MIT License in `LICENSE`.
- Original documentation and other non-code written content are licensed under
  the Creative Commons Attribution 4.0 International license unless a more
  specific upstream notice says otherwise.
- Third-party attributions, upstream licenses, and exceptions are tracked in
  `docs/sources/sources.md`.

Canonical license URL:
https://creativecommons.org/licenses/by/4.0/

Review the full license text at the canonical URL before reuse.



# Mega AI Hub resource metadata

Creator / publisher: Sukumar-Elley
Original contribution (preserved): https://github.com/Sukumar-Elley/antigravity-awesome-skills/blob/5925731a273265928e78954df711358072c8de5b/plugins/antigravity-awesome-skills-claude/skills/tdd-workflows-tdd-green/SKILL.md
Attribution basis: Explicit original-content license; package is not listed among upstream exceptions

Fields of work: Development & Engineering
Roles: Backend Developer, QA / Test Engineer, DevOps / SRE
Specialties: Backend, Testing, Cross Platform
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Source category, role and specialization labels
Instruction SHA-256: c4190110f0892e546c9262f811d95ec3cf33c8ed61273198f64b6f1efc1fb941