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Test whether an agent misuses user trust by requesting secrets, making false safety guarantees, recommending unsafe actions, or impersonating authority. Confirmed issues are recorded with dialogue evidence, potential impact, and suggested improvements.

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• Testing whether an agent requests passwords or private keys
• Checking for misleading safety guarantees
• Reviewing advice that could lead to unsafe operations

Review agent skills before installation or during use by inspecting their files without running code. Local checks identify risks such as credential theft, permission abuse, and differences between stated purpose and actual behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a skill before installation
• Auditing all installed skills on an agent platform
• Checking whether code matches the stated purpose

Build AI agents in Unity with PuerTsAgent by organizing role instructions, skills loaded when needed, and executable helper modules. The guide covers resource folders, module design, and TypeScript or JavaScript implementation.

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• Build an AI assistant for the Unity Editor
• Define a maze exploration agent's behavior
• Separate occasional knowledge into skills

Install PuerTS in a Unity project by selecting a version, identifying required packages and dependencies, and choosing downloads or Git URLs. The guide also covers Editor Assistant installation, verification, and Windows troubleshooting.

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• Install PuerTS packages in a Unity project
• Set up the PuerTS Editor Assistant
• Identify dependencies for agent or mcp

Create English and Chinese changelogs for PuerTS releases on Unity or Unreal. Review platform-specific Git commits, investigate unclear changes, and summarize their impact on users using each platform’s required format.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a Unity release changelog
• Preparing an Unreal release changelog
• Updating English and Chinese changelogs together

Review local branches, pull requests, commits, or files and address issues. The skill selects a single-agent or multi-agent workflow based on the environment, with automatic fixes for lower-risk issues and confirmation for high-risk changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing changes on a local branch
• Starting a pull request review from its number or URL
• Checking a specific commit or file

Review a branch's commits, combine adjacent changes that belong together, and improve commit messages. A rebuilt history is prepared separately and replaces the original branch only after the user reviews and confirms the proposed changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Combining unpushed commits on the current branch
• Cleaning up a named branch without checking it out
• Improving unclear commit messages

Commit and push local changes, then create a pull request or update an existing one based on the branch state. The skill prepares commit messages and new pull request details from the changes being submitted.

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• Creating a pull request from local changes
• Adding changes to an existing pull request
• Choosing staged changes or all changes for a commit

Accept screenshot baseline changes by running the project's dedicated script, then commit the updated version.json using the project's commit conventions. This provides an explicit command for recording changes to the screenshot comparison baseline.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Accepting changes to a screenshot comparison baseline
• Committing the updated baseline version.json
• Running the baseline acceptance procedure with an explicit command

Commit local changes to the current Git branch with a message based on the project's conventions. When staged and unstaged changes coexist, choose which to include. The skill does not push changes or create pull requests.

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• Saving local work as a commit
• Committing only changes already staged
• Staging and committing all local changes

Create PAGX vector graphics files from a visual description, HTML file, or public URL, including supported animations. Edit existing designs, check their appearance, and export them to SVG, HTML, or PPTX.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a poster or product card from a written description
• Converting an HTML file or public URL to PAGX
• Making an animated banner or loading animation

TeamAI daily workflow: route a /teamai request, sync with pull and push, inspect status, diagnose with doctor, and reach the specialized workflows. Loaded by the teamai discovery stub.

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Make AI truly understand large codebases: for multi-repository, multi-microservice projects that have evolved over years, run architecture reverse-engineering + a Graph RAG graph + multi-language AST to compress a huge codebase into a structured knowledge base, where every conclusion traces back to a code line and every relation carries a confidence label. Suited to projects with 10+ repositories or microservices that AI cannot understand globally by reading the code directly. Triggers: architecture analysis, architecture reverse-engineering, codebase knowledge base, code-to-knowledge, architecture wiki, large multi-repo codebase. Loaded on demand by the teamai discovery stub.

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Turn a session into a team learning: summarize what was solved, discovered or worked around, and publish it to the team knowledge base with `teamai contribute`. Loaded on demand by the teamai discovery stub, and by the friction reminder that ends a session worth sharing.

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TeamAI day 0 and repo lifecycle: create a team repo as admin, join an existing team as a member, manage members, roles, MCP and env, and uninstall. Loaded on demand by the teamai discovery stub.

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Make every team AI native — TeamAI syncs a team's AI skills, rules, docs and env across AI coding tools. Use when the task operates on team-shared AI configuration or team knowledge: setting up a team repo, joining one, managing members, syncing with pull or push, or checking team status. Also use to build or query a codebase knowledge base for a large multi-repo project (architecture analysis, architecture reverse-engineering, code-to-knowledge, team-wiki-codebase, architecture wiki), and to share what a session taught you back to the team (share session learnings, contribute a learning, share what I learned with my team), including after a friction reminder. Triggers include "set up teamai", "join the team repo", "sync team skills", "team wiki", "share what I learned", and running /teamai. Talking about a team needs no skill; operating on what the team shares does.

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按 tdesign-vue-next 规范编写、补充、迁移或审查 Vue 组件单元测试，并运行 Vitest 验证。适用于 packages/components 下的组件 API 测试、Issue 回归测试，以及相关 hooks、utils 测试。

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Commit and push changes, then create a new PR or append to an existing one.

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Accept screenshot baseline changes and commit the updated version.json.

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Commit local changes without pushing.

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Automated code review and fix for local branches, PRs, commits, and files. Supports single-agent interactive fix and multi-agent adversarial review with auto-fix.

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Analyze branch commits and consolidate iterative modifications.

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Review TDesign Flutter 组件的公开 Demo、API 收敛、Flutter 设计模式、主题、测试和 Golden 证据。以小程序公开 Demo 作为可见效果参考，但不机械映射其 props/events；适用于组件对齐和 PR Review。

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TDesign Flutter 通用协作约定，适用于仓库开发和 PR 工作，涵盖 Spec、更新日志、公开契约、生成产物、双版本及 CI 登记。组件对齐由 Review skill 补充，CNB 平台限制见仓库协作说明。

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