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create-hat-collectioncreate HAT collection 搜索

Agent Skill

create-hat-collection 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

734

周安装

30

GitHub Stars

2,802

下载量

238
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

3

许可证

MIT

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:create-hat-collection(create HAT collection 搜索)
来源仓库:https://github.com/mikeyobrien/ralph-orchestrator
仓库路径:skills/create-hat-collection
安装命令:
npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill create-hat-collection
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill create-hat-collection

简介

用于查找、检索和筛选相关信息,适合根据关键词或任务场景快速定位候选结果。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境,支持多 Agent 工作流配置。
  • 通过命令行安装,需结合来源仓库文档核验具体用法,确保输出结构化 YAML 预设。
  • 安装前建议确认权限范围,避免触发未授权的联网或文件操作。
  • create-hat-collection 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Create Hat Collection

Overview

This skill generates Ralph hat collection presets through a guided, conversational workflow. It asks clarifying questions about your workflow, validates the configuration against schema constraints, and produces a production-ready YAML preset file.

Output: A complete .yml preset file in the presets/ directory.

When to Use

  • Creating a new multi-agent workflow from scratch
  • Transforming a workflow idea into a structured preset
  • Need guidance on hat design patterns and event routing

Not for: Modifying existing presets (use /creating-hat-collections reference instead)

Workflow

Phase 1: Understand the Workflow

Ask clarifying questions to understand:

  1. Purpose: What problem does this workflow solve?
  2. Pattern: Which architecture pattern fits best?

- Pipeline: A→B→C linear flow (analyze→summarize) - Critic-Actor: One proposes, another critiques (code review) - Supervisor-Worker: Coordinator delegates to specialists - Scientific: Observe→Hypothesize→Test→Fix (debugging)

  1. Roles: What distinct agent personas are needed?
  2. Handoffs: When should each role hand off to the next?
  3. Completion: What signals the workflow is done?

Phase 2: Design Event Flow

Map the workflow as an event chain:

task.start → [Role A] → event.a → [Role B] → event.b → [Role C] → LOOP_COMPLETE
                                                    ↓
                                         event.rejected → [Role A]

Constraints to validate:

  • Each trigger maps to exactly ONE hat (no ambiguous routing)
  • task.start and task.resume are RESERVED (never use as triggers)
  • Every hat must publish at least one event
  • Chain must eventually reach LOOP_COMPLETE

Phase 3: Generate Preset

Create the YAML file with these sections:

# <Preset Name>
# Pattern: <Architecture Pattern>
# <One-line description>
#
# Usage:
#   ralph run --config presets/<name>.yml --prompt "<example prompt>"

event_loop:
  starting_event: "<first.event>"  # Ralph publishes this

hats:
  hat_key:
    name: "<Emoji> Display Name"
    description: "<Short description of the hat's purpose>"
    triggers: ["event.triggers.this"]
    publishes: ["event.this.publishes", "alternate.event"]
    default_publishes: "event.this.publishes"
    instructions: |
      ## <HAT NAME> MODE

      <Clear role definition - what this hat does>

      ### Process
      1. <Step one>
      2. <Step two>
      3. Publish appropriate event

      ### Event Format

<event topic="event.name"> key: value </event>


      ### DON'T
      - <Common mistake to avoid>
      - <Another mistake>

Schema Reference

Required Top-Level Fields

FieldDescription
event_loop.starting_eventFirst event Ralph publishes

Hat Definition Fields

FieldRequiredDescription
nameYesDisplay name with optional emoji (e.g., "🔍 Analyzer")
descriptionYesShort description of the hat's purpose (one sentence)
triggersYesEvents this hat responds to (list)
publishesYesEvents this hat can emit (list)
default_publishesRecommendedFallback event if hat forgets to publish
instructionsYesRole-specific prompt (use `\` for multiline)

Fields That DON'T Exist

Never use these—they're not in the schema:

  • emoji (put emoji in name instead)
  • system_prompt (use instructions)
  • subscriptions / publications (use triggers / publishes)

Event Naming Conventions

<phase>.ready / <phase>.done      # Phase transitions
<thing>.approved / <thing>.rejected  # Review gates
<noun>.found / <noun>.missing     # Discovery events
<action>.request / <action>.complete # Request-response

Examples: analysis.complete, review.approved, build.blocked, spec.rejected

Validation Checklist

Before finalizing the preset, verify:

  • Each trigger maps to exactly ONE hat
  • No hat uses task.start or task.resume as triggers
  • Every hat has name, description, triggers, publishes, and instructions
  • default_publishes is set for hats with multiple publish options
  • Event chain can reach LOOP_COMPLETE
  • No orphan events that never get handled (warning only)
  • Instructions include role definition, process steps, event format, and DON'Ts

Output Location

Save generated presets to: presets/<name>.yml

For minimal/embedded presets: presets/minimal/<name>.yml

Testing the Preset

After generation, test with:

# Dry run to validate config parsing
cargo run --bin ralph -- run -c presets/<name>.yml -p "test prompt" --dry-run

# Run smoke tests
cargo test -p ralph-core smoke_runner

Use /evaluate-presets for comprehensive validation.

Example Conversation

User: I want a preset for doing code reviews with a security focus.

Assistant: I'll help create a security-focused code review preset. Let me ask a few questions:

  1. Review depth: Should this be a quick scan or thorough analysis?
  2. Roles needed: I'm thinking: Does this cover your needs, or should we add/remove roles?

- Security Analyst (finds vulnerabilities) - Code Reviewer (checks logic/style) - Summarizer (creates final report)

  1. Iteration: If issues are found, should the code be fixed, or just reported?

User: Thorough analysis, those roles work, just report issues don't fix.

Assistant: Here's the event flow I'm designing:

task.start → [Security Analyst] → security.complete
                                        ↓
          → [Code Reviewer] → review.complete
                                        ↓
          → [Summarizer] → LOOP_COMPLETE

Let me generate the preset...

[Generates YAML with three hats following the schema]

Common Patterns Reference

Pipeline (Sequential)

A → B → C → done

Use for: analysis workflows, document processing

Critic-Actor (Review Loop)

Actor → Critic → approved/rejected
                    ↓
         rejected → Actor (retry)

Use for: code review, quality gates

Supervisor-Worker

Supervisor → worker.task → Worker → work.done → Supervisor

Use for: complex task decomposition

Scientific Method

Observe → Hypothesize → Test → confirmed/rejected
                                    ↓
                         rejected → Observe

Use for: debugging, investigation

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

04

需要参考平台分布和安装热度时

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

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21.69%
按下载量换算52

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17.61%
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windsurf

13.52%
按下载量换算32

trae

7.71%
按下载量换算18

Codex

3.23%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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