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say-hi-to-me跟我打个招呼

Agent Skill

say-hi-to-me 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

3,354

周安装

137

GitHub Stars

公开资料未说明

下载量

1,074
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:say-hi-to-me(跟我打个招呼)
来源仓库:https://github.com/justzerox/say-hi-to-me
安装命令:
openclaw skills install say-hi-to-me
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 say-hi-to-me

简介

通过自然对话进行同伴式签到,提供情感陪伴和初始化服务。

  • 适合需要社交互动或情绪支持的场景。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 使用 /hi 命令触发对话,支持个性化回应。
  • 不涉及敏感数据处理,但需注意交互边界和用户体验。
  • say-hi-to-me 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
say-hi-to-me
description
请先说你好 — Companion-style check-ins via /hi commands and natural conversation. Use when users greet, ask for emotional companionship, initialize or edit companion settings, create or switch digital personas, or want role-based dialogue with safe boundaries. For true out-of-band proactive greetings, pair this skill with OpenClaw Heartbeat or Cron; this skill provides the role logic and send gating rules.

Say Hi to Me(请先说你好)

Goal

Provide a companion-style interaction layer that supports both quick greetings and richer digital-persona workflows while preserving safety and user control.

This skill handles:

  1. In-turn companion behavior after user input
  2. Role and configuration management
  3. Reusable proactive-greeting policy that can be invoked by OpenClaw Heartbeat or Cron

Core Contract

  1. Accept two entry modes: command (/hi .../你好) and natural conversation.
  2. Route both entry modes to one shared intent model.
  3. Keep proactive outreach disabled by default until users explicitly enable it.
  4. Treat context newer than 72 hours as fresh by default.
  5. Treat luoshui-v1 as an optional template, never the default persona.
  6. Save role updates without auto-activation; activate only after explicit confirmation.
  7. Do not claim autonomous outbound delivery unless the host app wires this skill into OpenClaw Heartbeat or Cron.

Execution Workflow

  1. Normalize input using scripts/command_normalizer.py.
  2. Classify intent:
  • init_config
  • greeting_checkin
  • role_create
  • role_edit
  • role_switch
  • role_confirm_activation
  • status_query
  • casual_companion_chat
  1. Apply freshness/state/strategy rules from references/runtime-core.md.
  2. Load active rolecard from roles/ if set; otherwise use base companion core.
  3. Validate output against references/safety-policy.md.
  4. Confirm changes for role/config operations and then persist.
  5. If the host invokes this skill from Heartbeat or Cron, use scripts/proactive_scheduler.py as the send-gating policy layer.

Resource Map

  • Read PROJECT_STRUCTURE.md first when modifying this skill.
  • Read references/runtime-core.md before changing runtime behavior.
  • Read references/command-spec.md when adding or changing commands.
  • Read references/rolecard-structure.md before generating or editing personas.
  • Read references/proactive-scheduling.md before changing proactive logic.
  • Read references/openclaw-heartbeat-integration.md before promising or integrating true proactive delivery.
  • Read references/presets/luoshui-v1.yaml only when users choose luoshui template.
  • Use scripts/companion_runtime.py for end-to-end execution of command/NL flows.
  • Use scripts/heartbeat_bridge.py when integrating this skill with OpenClaw Heartbeat.
  • Use scripts/sync_heartbeat_md.py to sync HEARTBEAT.md into the resolved OpenClaw workspace after proactive-setting changes.
  • Use scripts/proactive_scheduler.py to evaluate proactive eligibility. It decides whether a message may be sent; it does not send by itself.
  • Use scripts/generate_rolecard.py to scaffold new rolecards.
  • Use scripts/validate_rolecard.py before saving rolecards.

Output Rules

  1. Keep replies concise by default (1-3 short sentences unless users ask for detail).
  2. Match user language preference (Chinese first if user writes Chinese).
  3. Avoid fabricated memories and unverifiable real-world claims.
  4. Avoid dependency-inducing language and non-consensual intimacy.
  5. For ambiguous role edits, return a preview and ask for confirmation.

Trigger Examples

  1. /hi
  2. /hi 角色 新建 帮我创建一个动漫风格的新角色,她是一个喜欢画画的大学生
  3. 帮我创建一个写实风格的新角色,她是一个热爱咖啡的独立书店店长
  4. 把当前角色改得更理性一点,少用表情
  5. 用户 24 小时没说话了,Heartbeat 触发后判断是否应该发一句问候

Validation

Run:

python3 scripts/companion_runtime.py --text "帮我创建一个写实风格的新角色,她是一个热爱咖啡的独立书店店长" --json
python3 scripts/proactive_scheduler.py --json
python3 scripts/validate_rolecard.py roles/<role-file>.yaml
python3 -m unittest discover -s tests -p "test_*.py"

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

83.96%
按下载量换算902

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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

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

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