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goga-cell-python
Python rules for implementing CODEMANIFEST contracts
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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Python rules for implementing CODEMANIFEST contracts
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Verify each Cell's CODEMANIFEST against the implementation
Generate the final acceptance report with verdict
Defines the acceptance scope — the set of cells for a given functionality
Final acceptance orchestrator for contract-oriented workflows
Cell test coverage assessment for acceptance review
Validate cell-level usage files against actual implementation during acceptance
Basado en la clasificación ocupacional SOC
| name | goga-cell-python |
| description | Python rules for implementing CODEMANIFEST contracts |
Language skill for Python.
Apply the specification within the context of the invoking skill. Do not paraphrase the content — use it for decision-making.
Invoke via the goga-lang-disp router.
Full CODEMANIFEST example for Python with all DSL constructs:
Imports:
- Types:
- DataModel
- BaseConfig AS Config
Usages:
- serialization
From: path/to/data_cell
Usages:
conventions: .goga/usages/python_conventions.md
pattern: |
All public methods must use type hints. Return values are immutable where possible.
testing: |
Each routine and entity method must have a corresponding test in tests/.
Annotations: |
Use `conventions` for code style.
Use `testing` for test requirements.
Use `serialization` from Imports for data encoding patterns.
All methods must return concrete types, not `Any`.
---
"parse_input(input: str) -> data: bytes":
location: parser.py
annotations: |
Parse raw input string into structured data.
`input`: raw string to parse
Use `pattern` for implementation.
"DataProcessor(config: Config)":
location: processor.py
annotations: |
Process data according to configuration.
`config`: processor configuration from `Config` type.
Use `serialization` from Imports for encoding.
Use `conventions` for code style.
properties:
"name -> str": |
Processor identifier.
"buffer_size -> int": |
Maximum buffer size in bytes.
methods:
"process(data: list[T]) -> result: list[T]": |
Process a batch of data items.
`data`: input items to process
`result`: processed items
Use `pattern` for implementation.
"reset()": |
Reset internal state.
"BaseHandler::HTTPHandler(host: str)":
location: handler.py
annotations: |
HTTP-specific handler extending BaseHandler.
`host`: server hostname
Use `serialization` from Imports for request/response encoding.
->DataModel: {}
---
Author: Goga
CreatedAt: 22/05/26
Description: |
Example CODEMANIFEST demonstrating all DSL constructs for Python.
A cell is a Python package:
cell/
├── CODEMANIFEST
├── __init__.py
Facade: __init__.py must expose the full contract API through __all__. Only identifiers listed in
__all__ constitute the cell facade.
Naming: PascalCase for classes; snake_case for functions, methods, and properties.
Constructors: The entity signature describes __init__ (the self parameter is excluded from the contract).
Type hints: mandatory. Type annotations drive signature extraction for properties and methods.
| Python | CODEMANIFEST | Note |
|---|---|---|
class in __all__ | Entity | Class exported through __all__ |
def at module level in __all__ | Routine | Function exported through __all__ |
@property in class | Property | Type extracted from return annotation |
def method in class | Method | self excluded from signature |
__init__ parameters | Entity signature | self excluded |
Allowed:
str, int, float, bool,
list[T], dict[str, T],
T | None
Forbidden:
*args, **kwargs,
dict without generics,
list without generics
"dynamic_signature(...args: str, ...kwargs: dict) -> value:str":
annotations: |
Dynamic parameters example
`args`: non-keyword, positional arguments (*args)
`kwargs`: keyword, named arguments (**kwargs)