agentleFS
ss2codess2code/nanoclaw-ops/.claude/skills/init-first-agent/SKILL.md

init-first-agent

Skill1 starsChanged 40 days agoMITView on GitHub

Walk the operator through creating the first NanoClaw agent for a DM channel — resolve the operator's channel identity, wire the DM messaging group to a new agent, and trigger a welcome DM via the normal delivery path. Use after channel credentials are configured and the service is running.

  • Reads credentials

7 other projects use a version of this, 7 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use add-anydoc, add-clidash and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • TomGranotSkill

    add-anydoc

    Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.

    Also in 5 projects that use this

  • TomGranotSkill

    add-clidash

    Add clidash — a zero-dependency, read-only web dashboard that derives its tabs and tables at runtime from any CLI that lists resources as JSON. Ships pre-wired for NanoClaw's ncl CLI (agent groups, sessions, channels, users, roles), plus message-activity charts, a log tail, and a read-only file viewer for group skills/CLAUDE.md/profiles.

    Also in 5 projects that use this

  • qwibitaiSkill

    add-iron-proxy

    Install or refresh Iron Proxy and its official Iron Control web console for NanoClaw. Use when selecting the Iron gateway, adding its management UI, configuring credentials and grants, or restoring the proxy, approval bridge, and agent guidance.

    Also in 4 projects that use this

  • qwibitaiSkill

    add-mattermost

    Add a self-hosted or cloud Mattermost bot channel through the Chat SDK bridge, reusing a healthy server when available and linking to official server setup guidance when needed.

    Also in 4 projects that use this

  • nanocoaiSkill

    add-cursor

    Use Cursor (local Agent SDK) as a full agent provider — planning, tool orchestration, MCP tools, session resume — alongside or instead of Claude. Cursor-account sign-in or API key, held by the credential gateway. Per-group via `ncl groups config update --provider cursor`. Distinct from using Cursor as a cloud agent (those run on Cursor VMs and are not this provider).

    Also in 3 projects that use this

  • +5 more from TomGranot
  • +1 more from qwibitai

The file

We split this skill into the rules it gives an agent

8 rules. 4 are common, 0 are distinctive, and 4 are very specific to this project.

  • 4

    Common

    Most of the 7 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Service running: Check: launchctl list | grep "$(.

    line 12
  2. Very specific:

    Read src/channels/index.ts to find enabled channels (uncommented imports).

    line 18
  3. Very specific:

    Read the channel's own skill for its ## Channel Info > how-to-find-id section (e.g.

    line 26
  4. Common:

    Wait for the user's confirmation.

    line 54
  5. Very specific:

    Add --provider <name> when the user picked a non-default provider (there is no install-wide default — the choice is explicit per group).

    line 85
  6. Common:

    Do not tail the log or poll in a sleep loop.

    line 100
  7. Common:

    Wait for the user's reply.

    line 104
  8. Common:

    If they say it didn't arrive, then diagnose using the DB directly (no waiting loops required — the message either delivered or it didn't):

    line 106

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Init First Agent

Stand up the first NanoClaw agent for a channel and verify end-to-end delivery by having the agent DM the operator. Everything the skill does is idempotent — rerunning is safe.

Prerequisites

  • Service running. Check: launchctl list | grep "$(. setup/lib/install-slug.sh && launchd_label)" (macOS) or systemctl --user status "$(. setup/lib/install-slug.sh && systemd_unit)" (Linux). If stopped, tell the user to run /setup first.
  • Target channel installed. At least one /add-<channel> skill has run, credentials are in .env, and the adapter is uncommented in src/channels/index.ts.
  • Adapter connected. Tail logs/nanoclaw.log — look for a recent channel setup / adapter connected line for the target channel.

1. Pick the channel

Read src/channels/index.ts to find enabled channels (uncommented imports). Cross-check .env for the relevant credentials.

AskUserQuestion: "Which channel should host the welcome DM?" with one option per enabled channel (Discord, Slack, Telegram, WhatsApp, Webex, Teams, Google Chat, Matrix, iMessage, Resend, …).

Record the choice as CHANNEL (lowercase, e.g. discord).

2. Ask for the operator's identity

Read the channel's own skill for its ## Channel Info > how-to-find-id section (e.g. .claude/skills/add-discord/SKILL.md, .claude/skills/add-telegram/SKILL.md). Show those instructions to the user in plain text.

Then ask in plain text (NOT AskUserQuestion — these are free-form):

  1. Your user id on this channel — e.g. a Discord user ID, Telegram user ID, Slack user ID. Record as USER_HANDLE.
  2. Your display name — human name, used to name the agent group (dm-with-<normalized>) and as the welcome-message addressee. Record as DISPLAY_NAME.
  3. Agent persona name — the assistant's display name. Default: DISPLAY_NAME. Record as AGENT_NAME.

3. Resolve the DM platform id

This depends on whether the channel supports cold DM via adapter.openDM.

Channels without cold DM (direct-addressable): telegram, whatsapp, imessage, matrix, resend. The user handle doubles as the DM chat id. Set:

PLATFORM_ID=${CHANNEL}:${USER_HANDLE}

Skip to step 4.

Channels with cold DM (resolution-required): discord, slack, teams, webex, gchat. The bot can DM cold at runtime via Chat SDK, but this skill runs standalone — it can't call the adapter. Two resolutions:

3a. User DMs the bot once (Discord / Slack / Teams / Webex / gChat)

Tell the user:

Send any single message to the bot as a DM from your account on ${CHANNEL}. The router will record the DM as a messaging group. Reply done here when you've sent the message.

Wait for the user's confirmation. Then look up the most recent DM messaging groups:

pnpm exec tsx scripts/q.ts data/v2.db "SELECT id, platform_id, name, created_at FROM messaging_groups WHERE channel_type='${CHANNEL}' AND is_group=0 ORDER BY created_at DESC LIMIT 5"

Show the top rows to the user and confirm which platform_id is theirs (usually the most recent). Record as PLATFORM_ID. If none appeared, check logs/nanoclaw.log for unknown_sender drops — the adapter might be rejecting inbound due to connection or permission issues.

3b. Telegram pair-code path (if the user prefers not to DM first)

For Telegram only, there's an existing pair-code primitive. When you run this tool, take the output and extract the pairing code. Then show it to the user in plain text and ask the user to send the code in the Telegram chat to complete the pairing.

npx tsx setup/index.ts --step pair-telegram -- --intent new-agent:dm-with-<folder>

Parse the PAIR_TELEGRAM_ISSUED status block for CODE and follow the REMINDER_TO_ASSISTANT line in that block. Then wait for the PAIR_TELEGRAM block — read PLATFORM_ID and PAIRED_USER_ID from it. telegram.ts's interceptor has already upserted the user and granted owner if none existed yet. Use PLATFORM_ID and PAIRED_USER_ID directly in step 4.

4. Run the init script

First, pick the agent provider. Read src/providers/index.ts and collect the installed providers from its import './<name>.js'; lines — claude is always available as the built-in default. If a non-default provider is installed (e.g. codex), ask the user which one this agent should run on; if only claude is available, skip the question and omit the flag.

npx tsx scripts/init-first-agent.ts \
  --channel "${CHANNEL}" \
  --user-id "${CHANNEL}:${USER_HANDLE}" \
  --platform-id "${PLATFORM_ID}" \
  --display-name "${DISPLAY_NAME}" \
  --agent-name "${AGENT_NAME}"

Add --provider <name> when the user picked a non-default provider (there is no install-wide default — the choice is explicit per group). Add --welcome "System instruction: ..." to override the default welcome prompt.

The script:

  1. Upserts the users row and grants owner role if no owner exists.
  2. Creates the agent_groups row and calls initGroupFilesystem at groups/dm-with-<name>/.
  3. Reuses or creates the DM messaging_groups row.
  4. Wires them via messaging_group_agents (which auto-creates the companion agent_destinations row).
  5. Hands the welcome message to the running service via its CLI socket (data/cli.sock), targeting the DM messaging group. The service routes it into the DM session, which wakes the container synchronously. If the socket isn't reachable (service down), falls back to a direct inbound.db write that the next host sweep picks up.

Show the script's output to the user.

5. Verify

The welcome DM is queued synchronously; the only wait is container cold-start (~60s on first launch) before the agent processes the message and the reply flows through outbound.db to the channel.

Do not tail the log or poll in a sleep loop. Ask the user in plain text:

The welcome DM should arrive shortly. Let me know when you've received it (or if it doesn't arrive within two minutes).

Wait for the user's reply. If they confirm receipt, the skill is done.

If they say it didn't arrive, then diagnose using the DB directly (no waiting loops required — the message either delivered or it didn't):

  • pnpm exec tsx scripts/q.ts data/v2-sessions/<agent-group-id>/<session-id>/outbound.db "SELECT id, status, created_at FROM messages_out ORDER BY created_at DESC LIMIT 5" — check for stuck pending rows. Replace <agent-group-id> and <session-id> with the values from the script's output.
  • grep -E 'Unauthorized channel destination|container.*exited|error' logs/nanoclaw.log | tail -20 — look for ACL rejections or container crashes.
  • ls data/v2-sessions/<agent-group-id>/*/outbound.db — confirm the session exists.

Troubleshooting

"Missing required args" — the script wants --channel, --user-id, --platform-id, --display-name at minimum. Re-check the command you assembled.

No messaging_groups row appears after the user DMs (step 3a) — the router silently drops messages from unknown senders under strict policy but still creates the messaging_groups row. If the row is missing entirely, the adapter isn't receiving the inbound message. Check logs/nanoclaw.log for adapter errors (auth, gateway disconnect, rate limit).

Owner already exists — hasAnyOwner() returned true, so the grant is skipped silently. That's fine; the script still creates the agent and wiring. Reassigning ownership needs a separate flow (not this skill).

Wrong person got the welcome DM — the --platform-id you passed is someone else's DM channel. Rerun with the correct one; the script is idempotent on user/messaging-group/agent-group but writes a new session welcome each run.

Agent group name collision — if dm-with-<display-name> already exists (e.g. rerunning with the same display name), the script reuses it. Pass a different --display-name to get a distinct folder.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.