infrastructure-core
Skill for the core infrastructure module providing logging, configuration, exception handling, progress tracking, checkpoints, retry logic, pipeline execution, performance monitoring, security, file operations, and multi-project orchestration. Use when setting up logging, loading config, handling errors, running pipelines, or monitoring performance.
Best use case
infrastructure-core is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Skill for the core infrastructure module providing logging, configuration, exception handling, progress tracking, checkpoints, retry logic, pipeline execution, performance monitoring, security, file operations, and multi-project orchestration. Use when setting up logging, loading config, handling errors, running pipelines, or monitoring performance.
Teams using infrastructure-core should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/core/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How infrastructure-core Compares
| Feature / Agent | infrastructure-core | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Skill for the core infrastructure module providing logging, configuration, exception handling, progress tracking, checkpoints, retry logic, pipeline execution, performance monitoring, security, file operations, and multi-project orchestration. Use when setting up logging, loading config, handling errors, running pipelines, or monitoring performance.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Core Infrastructure Module
Foundation utilities used across the entire infrastructure layer and all project scripts.
## Logging (`logging_utils.py`)
```python
from infrastructure.core import get_logger, log_operation, log_stage, format_duration
from infrastructure.core.logging.setup import setup_logger
from infrastructure.core.logging.utils import log_timing, log_substep
logger = get_logger(__name__)
logger.info("Processing started")
# Decorators for automatic timing and logging
@log_operation("Processing data")
def process():
pass
@log_timing
def expensive_operation():
pass
# Structured progress logging
log_stage(1, 10, "Running Tests")
log_substep("Unit tests passed")
# ETA calculation
from infrastructure.core.runtime import calculate_eta
```
## Configuration (`config_loader.py`)
```python
from infrastructure.core.config.loader import load_config, find_config_file, get_config_as_dict
# Load project config.yaml
config = load_config(project_path / "manuscript" / "config.yaml")
# Auto-discover config file
config_path = find_config_file(project_root)
```
## Exception Hierarchy (`exceptions.py`)
All exceptions extend `TemplateError`. Use context-preserving helpers:
```python
from infrastructure.core import TemplateError
from infrastructure.core.exceptions import (
ConfigurationError, ValidationError, BuildError,
RenderingError, LLMError, PublishingError,
raise_with_context, chain_exceptions, format_file_context,
)
# Raise with file context
raise_with_context(ValidationError("Invalid format"), file_path="doc.md", line=42)
# Chain exceptions
try:
render()
except RenderingError as e:
chain_exceptions(BuildError("Pipeline failed"), e)
```
**Exception tree:** `TemplateError` → `ConfigurationError`, `ValidationError`, `BuildError`, `FileOperationError`, `DependencyError`, `TestError`, `IntegrationError`, `LLMError`, `LLMConnectionError`, `LLMTemplateError`, `RenderingError`, `FormatError`, `PublishingError`, `UploadError`, `LiteratureSearchError`, `APIRateLimitError`
## Pipeline Execution (`pipeline.py`)
```python
from infrastructure.core.pipeline import PipelineExecutor, PipelineConfig
config = PipelineConfig(project_name="my_project", core_only=True)
executor = PipelineExecutor(config)
result = executor.run()
```
## Checkpoint & Resume (`checkpoint.py`)
```python
from infrastructure.core import CheckpointManager
from infrastructure.core.runtime.checkpoint import PipelineCheckpoint
manager = CheckpointManager(checkpoint_dir)
manager.save(PipelineCheckpoint(stage=5, status="complete"))
checkpoint = manager.load() # Resume from saved state
```
## Progress Tracking (`progress.py`)
```python
from infrastructure.core import ProgressBar
from infrastructure.core.progress import SubStageProgress
progress = ProgressBar(total=100, prefix="Rendering")
progress.update(10)
```
## Retry Logic (`retry.py`)
```python
from infrastructure.core.runtime import retry_with_backoff
@retry_with_backoff(max_retries=3, base_delay=1.0)
def flaky_operation():
pass
```
## Performance Monitoring (`stage_monitor.py`, `function_profiler.py`)
```python
from infrastructure.core.runtime.function_profiler import CodeProfiler, monitor_performance
from infrastructure.core.pipeline.stage_monitor import PerformanceMonitor, get_system_resources
resources = get_system_resources()
monitor = PerformanceMonitor()
profiler = CodeProfiler()
def heavy_computation() -> None:
pass
with profiler.monitor("heavy_computation"):
heavy_computation()
```
## Security (`security.py`)
```python
from infrastructure.core.security import SecurityValidator, RateLimiter, rate_limit
from infrastructure.llm.core.sanitization import sanitize_llm_input
validator = SecurityValidator()
validator.validate_input(user_text)
sanitized = sanitize_llm_input(user_text)
@rate_limit(calls=10, period=60)
def api_call():
pass
```
## Environment Setup (`environment.py`)
```python
from infrastructure.core.runtime.environment import (
check_python_version, check_dependencies, check_build_tools,
setup_directories, verify_source_structure,
)
```
## File Operations (`file_operations.py`)
```python
from infrastructure.core.files.cleanup import clean_output_directory
from infrastructure.core.files.operations import copy_final_deliverables
clean_output_directory(output_path)
copy_final_deliverables(source, destination)
```
## Multi-Project Orchestration (`multi_project.py`)
```python
from infrastructure.core.pipeline.multi_project import MultiProjectConfig, MultiProjectOrchestrator
config = MultiProjectConfig(projects=["proj_a", "proj_b"])
orchestrator = MultiProjectOrchestrator(config)
result = orchestrator.run()
```
## Health Checks (`health_check.py`)
```python
from infrastructure.core import SystemHealthChecker
checker = SystemHealthChecker()
status = checker.get_health_status()
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