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GNN multi-format export generation. Use when exporting GNN models to JSON, XML, GraphML, GEXF, Pickle, or other interchange formats for use in external tools and frameworks.
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-export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.
正在显示 SKILL.md
| name | gnn-export |
| description | GNN multi-format export generation. Use when exporting GNN models to JSON, XML, GraphML, GEXF, Pickle, or other interchange formats for use in external tools and frameworks. |
Exports parsed GNN models to multiple interchange formats for interoperability with external tools, visualization platforms, and analysis frameworks.
# Run export
python src/7_export.py --target-dir input/gnn_files --output-dir output --verbose
# As part of pipeline
python src/main.py --only-steps 7 --verbose
| Format | Extension | Use Case |
|---|---|---|
| JSON | .json | General interchange, web tools |
| XML | .xml | Enterprise integration |
| GraphML | .graphml | Graph analysis tools (Gephi, yEd) |
| GEXF | .gexf | Dynamic graph visualization |
| Pickle | .pkl | Python-native serialization |
from export import (
export_model,
generate_exports,
export_single_gnn_file,
Exporter,
MultiFormatExporter,
get_supported_formats,
export_to_json,
export_to_xml,
export_to_graphml,
export_to_gexf,
process_export,
)
# Export single file to all formats
export_single_gnn_file("model.md", "output/")
# Use the Exporter class
exporter = Exporter()
result = exporter.export_gnn_model(gnn_content, "json")
# Multi-format export
mf_exporter = MultiFormatExporter()
results = mf_exporter.export_to_multiple_formats(content, ["json", "xml", "graphml"])
# Query supported formats
formats = get_supported_formats()
# Run full export step (used by pipeline)
process_export(target_dir, output_dir, verbose=True)
export_model / export_single_gnn_file — export a single modelgenerate_exports — batch export for a directoryExporter / MultiFormatExporter — class-based export interfacesexport_to_json, export_to_xml, export_to_graphml, export_to_gexf — format-specificprocess_export — main pipeline processing functionoutput/7_export_output/This module registers tools with the GNN MCP server (see mcp.py):
export_single_gnn_filelist_export_formatsprocess_exportvalidate_export_format