Token导航 LogoToken导航TokenDH.com
开发执行命令clawhub未标认证来源可访问clear审计通过

agently-playbookAgent 剧本

Agent Skill

agently-playbook 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

4,467

周安装

188

GitHub Stars

公开资料未说明

下载量

1,564
OpenClaw

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

MIT-0

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:agently-playbook(Agent 剧本)
来源仓库:https://github.com/maplemx/agently-playbook
安装命令:
openclaw skills install agently-playbook
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install agently-playbook

简介

agently-playbook 辅助构建和管理模型驱动型助手与自动化工作流程。

  • 支持初始化、验证、优化或重构内部工具与评估系统。
  • 适用于复杂业务流程的编排与迭代开发场景。
  • 安装命令为 openclaw skills install agently-playbook,需项目目录写入权限。
  • 使用前请检查是否依赖特定运行时环境或第三方服务,避免部署失败。

SKILL.md

name
agently-playbook
description
Use when the user wants to build, initialize, validate, optimize, or refactor a model-powered assistant, internal tool, automation, evaluator, or workflow from a business scenario or common problem statement, including project-structure refactors or starter skeletons that may separate model setup, prompt config, and orchestration, even if the request also mentions a UI, app shell, or local model service such as Ollama, and it is still unclear whether the solution should stay a single request, add supporting capabilities, or become orchestration. The user does not need to mention Agently explicitly.

Agently Playbook

Use this skill first when the request still starts from business goals, refactor goals, product behavior, or broad model-app language.

The user does not need to say Agently, TriggerFlow, or any other framework term. Generic asks such as "build an assistant", "help me design an internal tool", or "create a validator for common problems" should still start here when the owner layer is unresolved.

Requests that also mention a UI, a web page, a desktop shell, or a local model service such as Ollama should still start here when the request is fundamentally about shaping a model-powered tool rather than only wiring one narrow capability.

Workflow

  1. Reduce the request into scenario and atomic goals.
  2. If the request is a project initialization or structure refactor, choose the owner layers, async boundary, and repo skeleton first.
  3. Choose the narrowest native Agently capability path.
  4. Name the concrete operations or primitives that should be used.
  5. Name the validation rule that proves the design stayed native-first.

Native-First Rules

  • default to async-first guidance for service code, streaming, TriggerFlow, and any path that may overlap work or benefit from cancellation
  • treat sync APIs as wrappers for scripts, REPL use, or compatibility bridges unless the host truly requires sync-only integration
  • when the request is a project-shape refactor, separate settings, prompts, services, domain contracts, workflow, and tests before discussing low-level implementation details

Capability Routing

  • model provider setup, settings-file-based model separation, or ${ENV.xxx}-backed settings loading -> agently-model-setup
  • request-side prompt design, prompt placeholder injection, or config-file prompt bridge -> agently-prompt-management
  • output schema and reliability -> agently-output-control
  • response reuse, metadata, or streaming consumption -> agently-model-response
  • session continuity or restore -> agently-session-memory
  • tools, MCP, FastAPIHelper, auto_func, or KeyWaiter -> agently-agent-extensions
  • embeddings, KB, or retrieval-to-answer -> agently-knowledge-base
  • branching, concurrency, waiting/resume, mixed sync/async orchestration, event-driven fan-out, process-clarity refactors, runtime stream, or explicit multi-stage quality loops -> agently-triggerflow
  • migration choice between LangChain and LangGraph -> agently-migration-playbook

Anti-Patterns

  • do not skip this playbook when the owner layer is unresolved
  • do not invent custom output parsers, retry loops, or orchestration first
  • do not let sync-first sample code dictate the service architecture when the target is clearly async-capable
  • do not split project initialization into a fake standalone framework surface before the owner layers are chosen
  • do not treat multi-agent, judge, or review flows as separate framework surfaces before checking native Agently capabilities

Read Next

  • references/capability-map.md
  • references/project-framework.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

87.89%
按下载量换算1,375

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install agently-playbook 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。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

继续浏览同类 Skills