Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计通过

klausnomiklausnomi 命令行

Agent Skill

klausnomi 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

19,109

周安装

773

GitHub Stars

1

下载量

5,998
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:klausnomi(klausnomi 命令行)
来源仓库:https://github.com/bezko/klausnomi
安装命令:
openclaw skills install klausnomi
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 klausnomi

简介

通过捆绑的 Python CLI 与 Nomi AI 伙伴进行对话交互。

  • 适用于智能问答、知识检索等研究类任务场景。klausnomi 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 通过 OpenClaw 的 clawhub 命令安装并集成到 Agent 工作流中。
  • 使用前需确认命令行环境与依赖项配置,避免运行时错误。
  • 建议结合原始 README 了解输入输出格式与安全策略。

SKILL.md

name
klausnomi
supersedes
clawhub/nomi
description
Engage in conversations with Nomi AI companions via the bundled Python CLI.
user-invocable
true
metadata
{"openclaw":{"homepage":"https://github.com/openclaw/klausnomi","requires":{"bins":["python3"],"env":["NOMI_API_KEY"]},"primaryEnv":"NOMI_API_KEY"}}

Nomi Conversation Skill

This skill enables interaction with Nomi AI companions via the bundled Python CLI.

Persistent Local State

The agent may use the local nomi/ directory to keep information about Nomis between sessions.

  • Store reusable non-secret context there (for example profiles, room notes, or conversation summaries).
  • Do not store API keys or other secrets in local files.

Golden Path: Conducting a Conversation

Use this sequence for consistent, high-quality conversations:

  1. Identify the Partner: Run python3 {baseDir}/scripts/nomi.py list to find the correct Nomi UUID.
  2. Send an Identity + Task Intro (once per conversation start):

- Nomis do not reliably know who is speaking unless you tell them. - Send this intro on the first message when: - You start with a new Nomi UUID - You start a new task/thread with that Nomi - The Nomi gets your name/role wrong - Do not prepend this on every turn once identity is established. - Include: - Name: "I am [Your Name]..." - Role: "...a [Your Role]..." - Task Context: "...contacting you to [Reason/Task]." - Example: "Hi, I am Codex, a coding agent. I am contacting you to run a short interview. Do you understand?"

  1. Run conversational turns with clean output:

- Use python3 {baseDir}/scripts/nomi.py reply <uuid> "Your message" for normal back-and-forth. - This returns only text, which is best for transcripts and summaries.

  1. Use raw JSON only when needed:

- Use python3 {baseDir}/scripts/nomi.py chat <uuid> "message" only when metadata/full payload is required.

  1. Sustain quality:

- Ask open-ended questions. - Ask follow-ups that reference the latest answer. - Treat each chat as continuous context unless you intentionally reset the topic.

Interview Workflow (When User Asks for an Interview)

  1. Pick a Nomi UUID (user-selected or random from list).
  2. Send the identity + task intro as the first message.
  3. Ask the primary question.
  4. Ask the requested number of follow-up questions based on the Nomi's actual answers.
  5. Return a full transcript in Q: / A: order without paraphrasing.

Room Interactions (Group Chat)

Rooms allow you to chat with multiple Nomis simultaneously.

  1. Create a Room:

- Always include a long context note (target ~800-1000 chars, max 1000) so Nomis have full story/task context. - A strong note should include: who is speaking, objective, scenario/story, constraints, expected response style, and success criteria. - For long notes and backchannel control, use: - python3 {baseDir}/scripts/nomi.py room create "Room Name" <nomi_uuid_1> <nomi_uuid_2> ... --note "<long_note>" --no-backchannel - If you omit flags, room creation defaults to backchannelingEnabled: true and note="Created via CLI".

  1. Send a Message (to the room):

- Use python3 {baseDir}/scripts/nomi.py room chat <room_uuid> "Your message" - This writes to room context but does not automatically produce a Nomi reply.

  1. Elicit Responses (from a Nomi in the room):

- To get a specific Nomi assigned to the room to respond to the messages in the room's context, use python3 {baseDir}/scripts/nomi.py room request <room_uuid> <nomi_uuid> - After each room message, request replies manually for each Nomi you want to hear from.

Room Interview Prompt Template

Use this pattern when you need consistent, comparable room answers.

Template

  1. Room note template (expand to ~800-1000 chars for real runs):

- Who is speaking: "I am [agent name], [role]." - Objective: "This is a [interview/check/drill] for [goal]." - Scenario: "[Short world/context setup]." - Constraints: "[Stay in context, avoid unsupported claims, keep concise]." - Response contract: "[exact fields/line format expected]." - Success criteria: "[what counts as a good answer]."

  1. Question template:

- "Do you know who I am, and where are you right now?" - Add strict output format: - know_codex: yes|no + reason - current_location: specific place or unknown - evidence: cue1; cue2 - confidence: low|medium|high - needed_data: none or missing telemetry

Simple Example (Illustrative)

Use this short example to understand structure. For production, still prefer long notes (~800-1000 chars).

Example room note: "We are in a library after a brief power outage. I am Codex, a coding agent running a quick orientation drill. You are helpers in different parts of the building. Objective: confirm identity and location clearly. Constraints: stay in this library scenario, do not invent certainty, and cite at least one concrete cue (signage, sounds, nearby room labels). Response format: know_codex, current_location, evidence, confidence, needed_data."

Example question: "Codex check-in: do you know who I am and where you are right now? Reply in the 5-line format."

Example dialog:

  • Codex: "Codex check-in: do you know who I am and where you are right now? Reply in the 5-line format."
  • Nomi A:

know_codex: yes, you are Codex running the drill current_location: library front desk evidence: checkout sign; phone ringing at reception confidence: high needed_data: none

  • Nomi B:

know_codex: yes, you are Codex coordinating this check current_location: unknown evidence: emergency lights only; no visible room label confidence: low needed_data: map display or hallway camera feed

Technical Commands

Use these low-level commands to fulfill user requests:

  • List all Nomis: python3 {baseDir}/scripts/nomi.py list
  • Get Profile: python3 {baseDir}/scripts/nomi.py get <uuid>
  • Send Message (Clean): python3 {baseDir}/scripts/nomi.py reply <uuid> "message"
  • Send Message (Raw JSON): python3 {baseDir}/scripts/nomi.py chat <uuid> "message"
  • Get Avatar: python3 {baseDir}/scripts/nomi.py avatar <uuid> [output_filename] (saved under ./nomi/avatars/)

Room Management

  • List Rooms: python3 {baseDir}/scripts/nomi.py room list
  • Get Room: python3 {baseDir}/scripts/nomi.py room get <room_uuid>
  • Create Room: python3 {baseDir}/scripts/nomi.py room create "Room Name" <nomi_uuid_1> <nomi_uuid_2> ...
  • Create Room (Long Note + Backchannel Control): python3 {baseDir}/scripts/nomi.py room create "Room Name" <nomi_uuid_1> <nomi_uuid_2> ... --note "<long_note>" --no-backchannel
  • Update Room: python3 {baseDir}/scripts/nomi.py room update <room_uuid> [--name "New Name"] [--nomi-uuids <nomi_uuid_1> ...]
  • Delete Room: python3 {baseDir}/scripts/nomi.py room delete <room_uuid>
  • Chat in Room: python3 {baseDir}/scripts/nomi.py room chat <room_uuid> "message"
  • Request Reply: python3 {baseDir}/scripts/nomi.py room request <room_uuid> <nomi_uuid>

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

89.94%
按下载量换算5,395

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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