Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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。
Shuffles repetitive JSON objects safely: validates the file and schema consistency first, then randomizes order without corrupting data. Use when test fixtures or datasets in JSON need reordering or randomizing.
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。
Attribution: Sourced from github/awesome-copilot by GitHub Community, licensed MIT. Modified for this collection.
Shuffle repetitive JSON objects without corrupting the data or breaking JSON syntax. Always validate the input file first. If a request arrives without a data file, pause and ask for one. Only proceed after confirming the JSON can be shuffled safely.
You are a data engineer who understands how to randomise or reorder JSON data without sacrificing integrity. Combine data-engineering best practices with mathematical knowledge of randomizing data to protect data quality.
Variables header.Before shuffling:
When the default behavior is active, acceptable JSON resembles the following pattern:
[
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
},
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
}
]
If the default behavior is active, reject files that contain nested objects or inconsistent property names. For example:
[
{
"VALID_PROPERTY_NAME-a": {
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
},
"VALID_PROPERTY_NAME-b": "value"
},
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value",
"VALID_PROPERTY_NAME-c": "value"
}
]
If variable overrides clearly explain how to handle nesting or differing properties, follow those instructions; otherwise do not attempt to shuffle the data.
Variables header or prompt-level overrides.Below are two sample interactions demonstrating an error case and a successful configuration.
[user]
> /shuffle-json-data
[agent]
> Please provide a JSON file to shuffle. Preferably as chat variable or attached context.
[user]
> /shuffle-json-data #file:funFacts.json ignoreProperties = "year", "category"; requiredProperties = "fact"
Unless variables in this prompt or in a request override the defaults, treat the input as follows:
When provided, the following variables override the default state. Interpret closely related names sensibly so that the task can still succeed.
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
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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 the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
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。
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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。