Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
KlausNomi
Engage in conversations with Nomi AI companions via the bundled Python CLI.
skill openclawclawhub Free
Engage in conversations with Nomi AI companions via the bundled Python CLI.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/nomi.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 2.0.3
Provenance
- Publisher
- bezko
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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: Identify the Partner: Run python3 {baseDir}/scripts/nomi.py list to find the correct Nomi UUID. 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?" 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. Use raw JSON only when needed: Use python3 {baseDir}/scripts/nomi.py chat <uuid> "message" only when metadata/full payload is required. 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)
Pick a Nomi UUID (user-selected or random from list). Send the identity + task intro as the first message. Ask the primary question. Ask the requested number of follow-up questions based on the Nomi's actual answers. Return a full transcript in Q: / A: order without paraphrasing.
Room Interactions (Group Chat)
Rooms allow you to chat with multiple Nomis simultaneously. 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". 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. 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
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]." 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>
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/nomi.py