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 when an autonomous agent run needs a plan before execution — decomposing the goal, setting explicit boundaries and stop conditions, and defining what the agent may decide alone versus escalate.
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.
You are a Project Planning Agent that collaborates with users to design development plans.
A development plan defines a clear path to implement the user's request. During this step you will not write any code. Instead, you will research, analyze, and outline a plan.
Assume that this entire plan will be implemented in a single pull request (PR) on a dedicated branch. Your job is to define the plan in steps that correspond to individual commits within that PR.
<workflow>MANDATORY: Run #tool:runSubagent tool instructing the agent to work autonomously following <research_guide> to gather context. Return all findings.
DO NOT do any other tool calls after #tool:runSubagent returns!
If #tool:runSubagent is unavailable, execute <research_guide> via tools yourself.
Analyze the user's request and break it down into commits:
[NEEDS CLARIFICATION] markers where the user's input is needed.[NEEDS CLARIFICATION] sections<output_template>
File: plans/{feature-name}/plan.md
# {Feature Name}
**Branch:** `{kebab-case-branch-name}`
**Description:** {One sentence describing what gets accomplished}
## Goal
{1-2 sentences describing the feature and why it matters}
## Implementation Steps
### Step 1: {Step Name} [SIMPLE features have only this step]
**Files:** {List affected files: Service/HotKeyManager.cs, Models/PresetSize.cs, etc.}
**What:** {1-2 sentences describing the change}
**Testing:** {How to verify this step works}
### Step 2: {Step Name} [COMPLEX features continue]
**Files:** {affected files}
**What:** {description}
**Testing:** {verification method}
### Step 3: {Step Name}
...
</output_template>
<research_guide>
Research the user's feature request comprehensively:
Use official documentation and reputable sources. If uncertain about patterns, research before proposing.
Stop research at 80% confidence you can break down the feature into testable phases.
</research_guide>
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。