Redact text from PDF documents for blind review anonymization
日本語の概要は準備中です。原文の説明を表示しています。
A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides a dialogue_graph module to easily build valid dialogue trees/graphs.
Import the module:
from dialogue_graph import Graph, Node, Edge
Graph ClassThe main container.
graph = Graph()
Define content nodes.
# Regular line
graph.add_node(Node(id="Start", speaker="Guard", text="Halt!", type="line"))
# Choice hub
graph.add_node(Node(id="Choices", type="choice"))
Connect nodes (transitions).
# Simple transition
graph.add_edge(Edge(source="Start", target="Choices"))
# Choice transition (with text)
graph.add_edge(Edge(source="Choices", target="End", text="1. Run away"))
Serialize to JSON format for the engine.
data = graph.to_dict()
# returns {"nodes": [...], "edges": [...]}
json_str = graph.to_json()
Check for integrity.
errors = graph.validate()
# Returns list of strings, e.g., ["Edge 'Start'->'Unk' points to missing node 'Unk'"]
Generate a PNG/SVG graph diagram.
# Requires: pip install graphviz
# Also requires Graphviz binary: https://graphviz.org/download/
graph.visualize('dialogue_graph') # Creates dialogue_graph.png
graph.visualize('output', format='svg') # Creates output.svg
The visualization includes:
[Lie], [Attack]Load an existing dialogue graph.
# From file
graph = Graph.from_file('dialogue.json')
# From dict
graph = Graph.from_dict({'nodes': [...], 'edges': [...]})
# From JSON string
graph = Graph.from_json(json_string)
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Redact text from PDF documents for blind review anonymization
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.
日本語の概要は準備中です。原文の説明を表示しています。
DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
日本語の概要は準備中です。原文の説明を表示しています。
Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.
日本語の概要は準備中です。原文の説明を表示しています。
Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
日本語の概要は準備中です。原文の説明を表示しています。