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GNN comprehensive analysis report generation. Use when creating summary reports from pipeline outputs, generating markdown or HTML reports, or producing executive summaries of model processing results.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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 command-line interface dispatch and health checks. Use when invoking the `gnn` CLI, validating subcommand availability, or checking command-line access to pipeline modules.
GNN LLM-enhanced analysis and model interpretation. Use when generating natural language descriptions of GNN models, getting AI-assisted model explanations, or performing LLM-powered analysis of Active Inference specifications.
GNN Language Server Protocol integration. Use when starting editor diagnostics, checking hover behavior, or validating LSP support for GNN files.
GNN Model Context Protocol processing and tool registration. Use when registering GNN operations as MCP tools, building MCP server configurations, or integrating GNN capabilities with LLM tool-use workflows.
GNN pipeline orchestration and configuration management. Use when configuring pipeline execution, setting step inclusion/exclusion, managing pipeline state, or customizing the 25-step execution flow.
| name | gnn-report-generation |
| description | GNN comprehensive analysis report generation. Use when creating summary reports from pipeline outputs, generating markdown or HTML reports, or producing executive summaries of model processing results. |
Generates comprehensive analysis reports from all upstream pipeline outputs including parsing results, validation reports, simulation outcomes, statistical analyses, and visualizations.
# Generate reports
python src/23_report.py --target-dir input/gnn_files --output-dir output --verbose
# As part of pipeline
python src/main.py --only-steps 23 --verbose
from report import (
process_report, generate_comprehensive_report,
analyze_gnn_file, generate_html_report,
generate_markdown_report, generate_report,
ReportGenerator, ReportFormatter,
get_module_info, get_supported_formats, validate_report
)
# Process report step (used by pipeline)
process_report(target_dir, output_dir, verbose=True)
# Generate comprehensive report
report = generate_comprehensive_report(pipeline_results)
# Use the ReportGenerator class
gen = ReportGenerator()
report = gen.generate(results)
# Format-specific generation
generate_html_report(data, output_path)
generate_markdown_report(data, output_path)
# Validate a report
is_valid = validate_report(report_data)
# Query supported formats
formats = get_supported_formats()
process_report — main pipeline processing functiongenerate_comprehensive_report / generate_report — report generationReportGenerator / ReportFormatter — report classesgenerate_html_report / generate_markdown_report — format-specificanalyze_gnn_file — file-level analysis for reportsvalidate_report / get_supported_formats — utilitiesoutput/23_report_output/pipeline_execution_summary.json at pipeline rootThis module registers tools with the GNN MCP server (see mcp.py):
generate_reportget_report_module_infolist_report_formatsprocess_reportread_report