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build-giselle-agent构建吉赛尔 Agent

Agent Skill

build-giselle-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

392

周安装

16

GitHub Stars

公开资料未说明

下载量

127
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:build-giselle-agent(构建吉赛尔 Agent)
来源仓库:https://github.com/giselles-ai/agent-container
仓库路径:skills/build-giselle-agent
安装命令:
npx skills add https://github.com/giselles-ai/agent-container --skill build-giselle-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/giselles-ai/agent-container --skill build-giselle-agent

简介

构建轻量级、文件导向的智能体产品原型。

  • 强调可见文件操作与状态快照连续性更新机制。
  • 参考 OpenClaw 交互体验设计,适配 Vercel 部署环境。
  • 修改现有应用时需同步阅读 update-playbook.md 指导规范。
  • build-giselle-agent 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Build and Update Giselle Sandbox Agent

Use this skill to help developers ship agent products that are legible, file-oriented, and easy to evolve.

The current quality bar is:

  • OpenClaw-like UX on Vercel
  • visible files, workspace state, and artifacts
  • snapshot-based continuity
  • updates that land as normal file diffs

Read in this order

Read only what you need.

  1. reference/current-capabilities.md
  2. reference/build-quickstart.md
  3. reference/build-recipes.md
  4. reference/snippets.md
  5. If the user is modifying an existing app, also read reference/update-playbook.md

Workflow

1. Determine the job shape

Figure out whether the user wants one of these:

  • a new app
  • an update to an existing agent app
  • a docs or positioning refresh around an existing app

If the user already named an example or product shape, do not ask broad discovery questions again. Move straight to the closest recipe.

2. Intake only what is necessary

When details are missing, ask only the minimum needed to build the right thing:

  1. App pattern Choices: workspace-report, agent-inbox, browser-tool, or a custom variation
  2. Agent runtime Choices: codex or gemini
  3. Surface Choices: web-only or web + Slack
  4. File expectations Clarify whether artifact downloads or visible file lists are required
  5. Scope Clarify whether this is a fresh build or a diff-first update

If a reasonable default is obvious from the repo context, use it and keep going.

Before generating code, make sure the developer knows how to get the cloud API key:

  1. Create an account at https://studio.giselles.ai
  2. Open the API key management page in Studio and issue a new API key
  3. Add it to .env.local as GISELLE_AGENT_API_KEY=<your-api-key>

The default Cloud API is studio.giselles.ai, so no extra base URL is needed unless the user is self-hosting.

3. Build from a recipe, not from scratch

Prefer one of the concrete recipes in reference/build-recipes.md:

  • workspace-report: best when the product story is files, artifacts, and downloads
  • agent-inbox: best when the product story is a real chat app surface
  • browser-tool: best when the product story is explicit DOM interaction

The recipe should drive the implementation shape. Do not invent a new structure unless the user's request truly does not fit any recipe.

4. Required implementation pieces

For any new app, make sure the result includes the core runtime wiring:

  • defineAgent(...) in lib/agent.ts
  • withGiselleAgent(...) in next.config.ts
  • a chat route that uses giselle({agent}) with AI SDK streaming
  • a UI that makes the runtime understandable to the end user

Use reference/snippets.md for canonical patterns instead of re-deriving them.

5. Preserve the product story

The app should make these ideas clear when relevant:

  • Files created by the agent are real outputs, not just implied chat state.
  • Working inputs belong in the workspace; user-facing deliverables belong in ./artifacts/.
  • The runtime is a real sandbox, not an invisible black box.
  • Snapshots preserve continuity after sandbox expiration.

For workspace-report style apps, artifact UX should default to runtime-discovered artifact events from the chat stream. If the user should be able to download agent-created artifacts, read the artifact parts from streamed chat messages and prefer provider-emitted download_url when present.

Use these files as the canonical implementation reference for artifact download flow:

  • examples/workspace-report-demo/app/chat-panel.tsx
  • packages/giselle-provider/src/ndjson-mapper.ts

If the current request would produce a chat-only experience with no visible file or artifact story, call that out and propose the smallest improvement that fixes it.

6. When browser tools are involved

If the agent needs to inspect or manipulate the DOM:

  • use @giselles-ai/browser-tool
  • wire useBrowserToolHandler()
  • add predictable data-browser-tool-id values
  • describe those UI structures precisely in agentMd

Do not add browser-tool complexity to apps that do not need it.

7. Updating an existing app

When the user asks to evolve an existing agent app:

  1. Inspect the current files and summarize the baseline briefly.
  2. Pick the smallest diff that accomplishes the requested change.
  3. Preserve the existing product shape unless the user wants a larger redesign.
  4. Keep workspace/artifact visibility intact while expanding capabilities.
  5. Verify with build, typecheck, and any targeted tests that fit the scope.

Read reference/update-playbook.md before making non-trivial updates.

8. Output contract

Always return:

  1. Which files changed
  2. Why those changes exist
  3. What verification was run
  4. What the next safe iteration would be

Important rules

  • Prefer the repo's current docs and examples over stale memory.
  • Do not default to a spreadsheet app. Choose the recipe that best matches the user's product story.
  • Treat artifact download and file visibility as first-class product features, not optional afterthoughts, when the use case depends on trust and inspectability.
  • Keep SKILL.md procedural and lean. Put details in references.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.15%
按下载量换算46

Claude

31.04%
按下载量换算39

Cursor

19.92%
按下载量换算25

Gemini CLI

9.48%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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