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GNN shared utility functions and helper modules. Use when working with common pipeline utilities, logging helpers, file I/O wrappers, path management, or pipeline template infrastructure.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation --skill gnn-shared-utilities命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Generalized Notation Notation (GNN) processing pipeline for Active Inference generative models. Use when working with GNN files, running the 25-step pipeline, parsing model specifications, generating simulations, or producing visualizations and reports from GNN model definitions.
GNN comprehensive test suite execution and management. Use when running tests, writing new test cases, checking coverage, debugging test failures, or validating pipeline correctness across all 25 GNN modules.
GNN graph and matrix visualization generation. Use when creating network graph plots, matrix heatmaps, state space diagrams, or other visual representations of GNN models.
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| name | gnn-shared-utilities |
| description | GNN shared utility functions and helper modules. Use when working with common pipeline utilities, logging helpers, file I/O wrappers, path management, or pipeline template infrastructure. |
Provides shared utility functions, helper modules, and common infrastructure used across all 25 pipeline steps. Includes logging, error handling, configuration, dependency validation, and the standardized pipeline template.
# Utils is a shared library — not run directly but imported by all pipeline steps.
# Validate pipeline dependencies
python -c "from utils import validate_pipeline_dependencies; validate_pipeline_dependencies()"
# Check optional dependency status
python -c "from utils import get_dependency_status; print(get_dependency_status())"
# Run pipeline health check
python -c "from utils import generate_pipeline_health_report; print(generate_pipeline_health_report())"
| Module | Key Exports | Purpose |
|---|---|---|
pipeline_template | log_step_start, log_step_success, log_step_error, log_step_warning | Visual step logging |
logging | PipelineLogger, setup_step_logging, StructuredLogger | Structured logging |
error_handling | ErrorRecoveryManager, PipelineErrorHandler, generate_correlation_id | Error handling & recovery |
configuration | config_loader, get_config_value, set_config_value, validate_config | Pipeline configuration |
dependency | DependencyValidator, DependencyAuditor, validate_pipeline_dependencies | Dependency management |
performance | PerformanceTracker, track_operation_standalone | Performance monitoring |
from utils import (
# Logging
PipelineLogger,
setup_step_logging,
setup_main_logging,
log_step_start,
log_step_success,
log_step_error,
log_step_warning,
StructuredLogger,
get_pipeline_logger,
# Error handling
ErrorRecoveryManager,
PipelineErrorHandler,
generate_correlation_id,
format_error_message,
get_recovery_manager,
# Configuration
config_loader,
get_config_value,
set_config_value,
validate_config,
load_config,
save_config,
# Dependencies
DependencyValidator,
validate_pipeline_dependencies,
check_optional_dependencies,
get_dependency_status,
# Performance
PerformanceTracker,
performance_tracker,
get_performance_summary,
# Pipeline utilities
parse_arguments,
validate_and_convert_paths,
get_output_dir_for_script,
validate_output_directory,
BaseProcessor,
ProcessingResult,
create_processor,
)
# Setup logging for a pipeline step
logger = setup_step_logging("step_name", verbose=True)
log_step_start(logger, "Processing started")
log_step_success(logger, "Processing completed")
# Configuration management
from pipeline.config import get_pipeline_config
config = get_pipeline_config()
validate_config(config)
# Dependency validation
validate_pipeline_dependencies()
# Performance tracking
with performance_tracker.track("operation_name"):
do_work()
This module registers tools with the GNN MCP server (see mcp.py):
get_environment_infoget_file_infoget_logging_infoget_system_infovalidate_dependencies