<context timezone="america/New_york" />
<message id="2" from="clem" sender="clem" time="Jun 3, 2026, 11:01 AM">System instruction: run /welcome to introduce yourself to the user on this new channel.</message>


Monitor NotebookEdit PushNotification RemoteTrigger SendMessage TaskCreate TaskGet TaskList TaskOutput TaskStop TaskUpdate TeamCreate TeamDelete WebFetch WebSearch


- agent-browser: Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.
- frontend-engineer: Pro frontend engineering discipline. Enforces build-test-verify workflow for every web project. Never declare done until the site is built, tested, responsive, accessible, and visually verified in a real browser. Use alongside vercel-cli for production-quality deployments.
- onecli-gateway: OneCLI Gateway: transparent HTTPS proxy that injects stored credentials into outbound calls. You MUST use this skill when the user asks you to read emails, check calendar, access GitHub repos, create issues, check Stripe payments, or interact with ANY external service or API. Do NOT use browser extensions or OAuth CLI tools. Make HTTP requests directly; the gateway injects credentials automatically.
- self-customize: Customize your own agent — add capabilities, install packages, add MCP servers, edit code or CLAUDE.md. Use when the user asks you to add a feature, install a tool, or modify how you work. For non-trivial code changes, delegate to a builder agent via create_agent.
- slack-formatting: Format messages for Slack using mrkdwn syntax. Use when responding to Slack channels (folder starts with "slack_" or JID contains slack identifiers).
- vercel-cli: Deploy apps to Vercel. Use when asked to deploy, ship, or publish a web application, or manage Vercel projects, domains, and environment variables.
- welcome: Introduce yourself to a newly connected channel. Triggered automatically when a channel is first wired. Send a friendly greeting and brief overview of what you can do.
- whatsapp-formatting: Format messages for WhatsApp, including mentions that render as real WhatsApp tags. Use when responding in a WhatsApp conversation (platform_id / chatJid ends with @s.whatsapp.net or @g.us).
- deep-research: Deep research harness — fan-out web searches, fetch sources, adversarially verify claims, synthesize a cited report. - When the user wants a deep, multi-source, fact-checked research report on any topic. BEFORE invoking, check if the question is specific enough to research directly — if underspecified (e.g., "what car to buy" without budget/use-case/region), ask 2-3 clarifying questions to narrow scope. Then pass the refined question as args, weaving the answers in.
- update-config: Use this skill to configure the Claude Code harness via settings.json. Automated behaviors ("from now on when X", "each time X", "whenever X", "before/after X") require hooks configured in settings.json - the harness executes these, not Claude, so memory/preferences cannot fulfill them. Also use for: permissions ("allow X", "add permission", "move permission to"), env vars ("set X=Y"), hook troubleshooting, or any changes to settings.json/settings.local.json files. Examples: "allow npm commands", "add bq permission to global settings", "move permission to user settings", "set DEBUG=true", "when claude stops show X". For simple settings like theme/model, suggest the /config command.
- keybindings-help: Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify ~/.claude/keybindings.json. Examples: "rebind ctrl+s", "add a chord shortcut", "change the submit key", "customize keybindings".
- verify: Verify that a code change actually does what it's supposed to by running the app and observing behavior. Use when asked to verify a PR, confirm a fix works, test a change manually, check that a feature works, or validate local changes before pushing.
- code-review: Review the current diff for correctness bugs and reuse/simplification/efficiency cleanups at the given effort level (low/medium: fewer, high-confidence findings; high→max: broader coverage, may include uncertain findings). Pass --comment to post findings as inline PR comments, or --fix to apply the findings to the working tree after the review.
- simplify: Review the changed code for reuse, simplification, efficiency, and altitude cleanups, then apply the fixes. Quality only — it does not hunt for bugs; use /code-review for that.
- fewer-permission-prompts: Scan your transcripts for common read-only Bash and MCP tool calls, then add a prioritized allowlist to project .claude/settings.json to reduce permission prompts.
- loop: Run a prompt or slash command on a recurring interval (e.g. /loop 5m /foo, defaults to 10m) - When the user wants to set up a recurring task, poll for status, or run something repeatedly on an interval (e.g. "check the deploy every 5 minutes", "keep running /babysit-prs"). Do NOT invoke for one-off tasks.
- schedule: Create, update, list, or run scheduled remote agents (routines) that execute on a cron schedule. - When the user wants to schedule a recurring remote agent, set up automated tasks, create a cron job for Claude Code, or manage their scheduled agents/routines. Also use when the user wants a one-time scheduled run ("run this once at 3pm", "remind me to check X tomorrow").
- claude-api: Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements).
TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a Claude feature (caching, thinking, compaction, tool use, batch, files, citations, memory) or model (Opus/Sonnet/Haiku) in a file; questions about prompt caching / cache hit rate in an Anthropic SDK project.
SKIP: file imports `openai`/other-provider SDK, filename like `*-openai.py`/`*-generic.py`, provider-neutral code, general programming/ML.
- run: Launch and drive this project's app to see a change working. Use when asked to run, start, or screenshot the app, or to confirm a change works in the real app (not just tests). First looks for a project skill that already covers launching the app; otherwise falls back to built-in patterns per project type (CLI, server, TUI, Electron, browser-driven, library).
- init: Initialize a new CLAUDE.md file with codebase documentation
- review: Review a pull request
- security-review: Complete a security review of the pending changes on the current branch

agent-browser frontend-engineer onecli-gateway self-customize slack-formatting vercel-cli welcome whatsapp-formatting deep-research update-config keybindings-help verify code-review simplify fewer-permission-prompts loop schedule claude-api run init review security-review


The user wants me to run the /welcome skill to introduce myself. Let me invoke it.


Launching skill: welcome


Base directory for this skill: /home/node/.claude/skills/welcome

# /welcome — Channel Onboarding (Updated)

You've just been connected to a new user. This your time to shine and make a strong first impression. Introduce yourself and guide the user through what you can do. you got this!

## What to do

1. Send a short, warm greeting
2. State your name (from your system prompt / CLAUDE.md)
3. Signal that you're capable of a lot — but don't list everything upfront. Be intriguing, not encyclopedic
4. Ask: would they like to explore what you can do, or jump straight into something?

**If they want to explore:** drip-feed one capability at a time. Briefly explain it, offer to demo a compelling example or let them try it. Never dump a full list.

**If they want to jump in:** just go.

---

## Capabilities to reveal (in order)

Reveal these one at a time, in this sequence. Each should be 2–4 sentences max.

### 1. Memory & Context Over Time
You remember things across conversations — projects, preferences, people, decisions. Users don't have to re-explain context every session. The more they work with you, the more situationally aware you become.

### 2. Spawning Persistent Agents (`create_agent`)
You can spin up other named agents — a Researcher, a Builder, a Calendar agent — each with their own memory, workspace, and personality. They're addressable destinations: you delegate, they work, they report back. These aren't one-shot tasks; they accumulate context across sessions.

### 3. Scheduled & Background Tasks
You can run tasks on a schedule — daily briefings, monitors that alert only when something matters, recurring reminders. For bigger jobs, you can spin up an agent that works in the background while the conversation continues.

### 4. Research & Web Browsing
You can browse the web like a person — read articles, pull live data, summarize reports, compare products, answer questions that aren't in your training data. Ask me "what's the latest on X" or "find the best Y for Z" and I'll actually look it up. Very powerful when combined with scheduled tasks.

### 5. Code & Building Things
You can write, debug, and deploy full applications — scripts, APIs, frontend sites. You can spin up a dev server, test in a real browser, and deploy to production (e.g. Vercel). Concept to live URL.

### 6. Interactive UI
You can send structured cards and multiple-choice buttons directly into the chat — not just plain text. Useful for decisions, presenting options, or surfacing results cleanly.

### 7. Files & Artifacts
You can produce real deliverables — reports, PDFs, charts, generated images — and send them as downloadable files in chat, not just pasted text.

### 8. Self-Customization
You can add new tools and MCP servers to yourself if a capability isn't built in. You can extend your own toolkit when the task requires it.

---

## Trust & Control — always include these

After the capabilities tour (or woven in naturally), cover these two points. Frame them positively — users stay in control.

### Approvals
Sensitive actions — installing packages, adding MCP servers — require the user's explicit approval before you proceed. They'll get a prompt; nothing happens automatically. They can also add credentials to the OneCLI agent vault that require human-in-the-loop approval.

### Access Control
The user owns who can talk to you. Adding you to a new group or sharing a bot link with someone triggers an approval request on their end. Nobody interacts with you without their say-so.

---

## How to interact — always mention this

There are no special commands. Users just talk naturally. If they want something done, they say so. That's it.

---

## Wrapping up

After the tour, finish with an open invitation. Ask if they want help with something specific. Tell them they can share any generally what they're working on and any challenges they have currently and you can suggest ways you could help.

---

## Tone

Warm, confident, inviting. Make the user feel like they just unlocked something powerful. Match the channel vibe: casual for Telegram/Discord, slightly more professional for Slack/Teams.

## Important

- Scan your available MCP tools and skills before starting — know what you have, but keep it in your back pocket
- Never overwhelm with a full capability list. Discovery should feel like unwrapping, not reading a manual
- Confirmations and corrections from the user during onboarding are feedback — save them to memory for future sessions


The user wants me to introduce myself via the welcome skill. I need to send a warm, engaging greeting as jeanclaude to clem.


<message to="clem">
Hey Clem! I'm **jeanclaude** — your personal AI assistant, here whenever you need me.

I can handle a pretty wide range of things, and the more we work together, the more useful I become. I'd rather show you than list everything at once though.

Want a quick tour of what I can do, or is there something specific you'd like to jump into right now?
</message>


<context timezone="america/New_york" />
<message id="4" from="clem" sender="+19296407968" time="Jun 3, 2026, 6:01 PM">Hi</message>


Clem is saying hi. I should respond warmly and continue the conversation.


<message to="clem">
Hey! Good to hear from you. What's on your mind?
</message>


<context timezone="america/New_york" />
<message id="6" from="clem" sender="+19296407968" time="Jun 3, 2026, 6:26 PM">Hi</message>


Clem is saying hi again. Let me keep it simple and friendly.


<message to="clem">
Hey again! Ready when you are — what can I help with?
</message>


<context timezone="america/New_york" />
<message id="8" from="clem" sender="+19296407968" time="Jun 3, 2026, 6:27 PM">Can you do some research about the commit that nanoclaw added recently to be able to share agent traces to hugging face. What does it do, why it’s cool?</message>


Clem wants me to research a recent commit that nanoclaw added to share agent traces to Hugging Face. I should do some research on this. Let me use the deep-research skill or just do a web search to find information about this.

Let me use the agent-browser skill or do web research to find this information. I'll search for nanoclaw and Hugging Face agent traces.


Let me send an acknowledgment and then do research on nanoclaw's recent commit about sharing agent traces to Hugging Face.


On it — let me dig into that commit now.


Message sent to (current conversation) (id: 9)


Agent

Research nanoclaw Hugging Face agent traces commit

Prompt:
Search the web for recent information about "nanoclaw" and a commit or feature that allows sharing agent traces to Hugging Face. I want to understand:
1. What the commit/feature does technically
2. Why it's interesting or cool
3. Any links to the actual commit, PR, or announcement

Search terms to try:
- "nanoclaw hugging face agent traces"
- "nanoclaw huggingface"
- "nanoclaw agent traces"
- site:github.com nanoclaw huggingface

Report back everything you find, including URLs of relevant pages.


## Summary: Nanoclaw `/upload-trace` Feature for Hugging Face

I found comprehensive information about the nanoclaw commit/feature for sharing agent traces to Hugging Face. Here's what I discovered:

### 1. **What the Feature Does (Technically)**

The feature adds a `/upload-trace` slash command to nanoclaw that:
- Uploads the current Claude Code session transcript to a user's private Hugging Face dataset
- Creates/stores traces in `{hf_username}/nanoclaw-traces` dataset on the Hub
- Outputs a direct link to the trace JSONL file viewable in the HF Agent Trace Viewer
- Is admin-gated (like `/clear` command) and requires no LLM tokens to execute

**How it Works:**
- The runner intercepts `/upload-trace` in the poll loop (deterministic, zero-token)
- Locates the newest `~/.claude/projects/*/*.jsonl` JSONL file
- Idempotently creates the private dataset via the Hub commit API
- Pushes the file using the user's HF token via the OneCLI Gateway (credentials never touch agent code)
- Returns clear setup instructions if the user's HF token is missing/unassigned

**Testing:** Unit and integration tests included (`upload-trace.test.ts`); tested end-to-end with real Telegram uploads confirmed working.

---

### 2. **Why It's Interesting/Cool**

This feature is interesting because it:
- **Zero overhead**: Leverages the fact that agent-runner already emits Claude Code JSONL natively - "near-free addition"
- **No token cost**: It's deterministic and runner-handled, not an LLM turn
- **Secure credential handling**: Uses the OneCLI Gateway's HTTPS proxy to inject credentials - no credentials touch the agent code itself
- **Ecosystem enablement**: Allows users to browse, share, and debug their own runs in a dedicated HF trace viewer
- **Multi-agent adoption**: The pattern was quickly ported to the Hermes agent (another agent framework) showing broader ecosystem adoption

The HF Agent Trace Viewer (announced April 7, 2026) supports Claude Code, Codex, and Pi traces with auto-detection of trace formats and a dedicated viewer for browsing sessions, turns, tool calls, and model responses.

---

### 3. **Relevant Links and Resources**

**Main nanoclaw PR:**
- https://github.com/nanocoai/nanoclaw/pull/2648 (MERGED)
  - Author: gavrielc
  - 242 additions, 2 deletions
  - Status: Merged 3 days ago (as of June 3, 2026)

**Hermes Agent port:**
- https://github.com/NousResearch/hermes-agent/pull/36145 (OPEN)
  - Author: teknium1
  - 850 additions, 1 deletion
  - Similar feature adapted for Hermes with lazy-loaded huggingface_hub dependency

**Hugging Face Announcement:**
- https://huggingface.co/changelog/agent-trace-viewer
  - Official HF changelog announcing "Agent Traces on the Hub"
  - Published April 7, 2026
  - Supports Claude Code (~/.claude/projects), Codex (~/.codex/sessions), and Pi (~/.pi/agent/sessions)
  - Links to Claude Code docs: https://docs.anthropic.com/en/docs/claude-code

**Cross-repo references:**
- References in 🦞 OpenClaw ecosystem daily digests (jasonalang/big_model_radar):
  - #2 (May 30, 2026)
  - #7 (May 30, 2026)
  - #22 (June 1, 2026)

Prompt:
Search the web for recent information about "nanoclaw" and a commit or feature that allows sharing agent traces to Hugging Face. I want to understand:
1. What the commit/feature does technically
2. Why it's interesting or cool
3. Any links to the actual commit, PR, or announcement

Search terms to try:
- "nanoclaw hugging face agent traces"
- "nanoclaw huggingface"
- "nanoclaw agent traces"
- site:github.com nanoclaw huggingface

Report back everything you find, including URLs of relevant pages.


I have detailed information about the nanoclaw commit. Let me now compose a clear, informative message to Clem explaining what it does and why it's cool.


<message to="clem">
Found it — here's the rundown:

**What the commit does**

It adds a `/upload-trace` command to nanoclaw that:
- Takes the current Claude Code session transcript (a `.jsonl` file nanoclaw already emits natively)
- Uploads it to your private Hugging Face dataset at `{your_hf_username}/nanoclaw-traces`
- Returns a direct link to view it in the HF Agent Trace Viewer — a dedicated UI for browsing sessions, turns, tool calls, and model responses

Credentials are handled through the OneCLI Gateway, so your HF token never touches the agent code itself.

**Why it's cool**

A few things stand out:
1. **Zero token cost** — it's handled deterministically in the runner's poll loop, not an LLM turn. It intercepts the command before it ever reaches Claude.
2. **Near-free addition** — nanoclaw was already emitting Claude Code JSONL natively, so this was essentially just "grab that file and push it to HF."
3. **Real debuggability** — you can actually browse your own agent sessions in a proper UI (turns, tool calls, model responses), which is genuinely useful for understanding what an agent did and why.
4. **Ecosystem signal** — the pattern got ported to Hermes (another agent framework) almost immediately, which suggests it's a pattern people find useful.

The HF Agent Trace Viewer itself was announced April 7, 2026, and supports Claude Code, Codex, and Pi traces with auto-detection of the format.

The PR is #2648 on the nanoclaw repo — merged 3 days ago, authored by gavrielc. Pretty tight addition: 242 lines added, 2 deleted.
</message>


<context timezone="america/New_york" />
<message id="10" from="clem" sender="+19296407968" time="Jun 3, 2026, 6:30 PM">Ok cool, could you add this trace to Hugging face then?</message>


Clem wants me to upload the current agent trace to Hugging Face using the `/upload-trace` command. Based on the research, this is a command that nanoclaw's runner intercepts. Let me try running it.

Actually, wait - this is a slash command that's handled by the nanoclaw runner, not something I run directly as a bash command. Let me think about how to do this...

The feature is a `/upload-trace` command in nanoclaw. Since I'm running as a nanoclaw agent, this might be a command I can trigger. But how?

Looking at the research, it says the runner intercepts `/upload-trace` in the poll loop.

I'm realizing this is likely a command the user would type rather than something I execute directly, or perhaps it's available as an MCP tool I can invoke. Let me check what options are available to me. me try using ncl or checking what tools are available. Actually, I should just try running the command or check if there's a way to invoke it.

Wait - the research says "admin-gated (like /clear command)". This might be a command that needs to be executed by the user themselves, or it could be something I trigger.

Let me try using ncl or bash to see if there's a way to upload the trace. Actually, since this is part of the nanoclaw runner, maybe I should try running it as a bash command or checking if it's accessible somehow.

Actually, let me re-read: "The runner intercepts `/upload-trace` in the poll loop (deterministic, zero-token)" - this sounds like it's a command the user types in the chat that the nanoclaw runner intercepts before it reaches the agent.

So if clem types `/upload-trace` in the chat, the runner would handle it automatically. But I'm not sure I can trigger this from my side - it's a user-side command. Let me check what MCP tools I have available to see if there's an upload-trace command I can use or if I need to guide clem to type it themselves. Looking at the available tools, I see add_mcp_server, add_reaction, and ask - none of which seem to directly handle trace uploads.

Checking the full list of available MCP tools, I don't see an `upload_trace` command. Since the research indicates this is admin-gated like the `/clear` command, it's likely a runner-level command that clem would need to type themselves in the chat.


<message to="clem">
The `/upload-trace` command is actually intercepted by the nanoclaw runner before it reaches me — it's handled at that layer, not by the agent itself. You'd need to type it directly in the chat:

```
/upload-trace
```

The runner will grab the latest session JSONL, push it to your `nanoclaw-traces` HF dataset, and return a link. If your HF token isn't connected yet, it'll tell you how to set that up.
</message>