lisa-openclaw-connect-staff

name

lisa-openclaw-connect-staff

description

Connect staff roles to a human chat surface (Telegram or Slack) via OpenClaw using a facilitator/specialist hub-and-spoke model. Registers bots/apps, creates or reuses the human-facing surface, wires routes in ~/.openclaw/openclaw.json, writes facilitator/specialist agent prompts, validates the gateway, resets stale sessions, and runs an end-to-end route test. Use when you want a "chief of staff" facilitator and its specialists reachable from chat. Requires lisa-openclaw-setup first.

lisa-openclaw-connect-staff

Wire existing staff roles into a working hub-and-spoke chat deployment on Telegram or Slack through OpenClaw. Humans talk only to the facilitator (the "chief of staff"); the facilitator consults specialists internally and synthesizes one answer back to the human.

This SKILL.md is the complete, runnable definition for both Claude Code and Codex. Codex has no command or $ARGUMENTS layer, so every behavior — including platform selection — is specified here. Keep all real values (org names, ids, handles, tokens, paths) out of any committed file; they belong only in ~/.openclaw/openclaw.json (machine-local, never committed).

Prerequisites

1. lisa-openclaw-setup has run (an openclaw section exists in .lisa.config.json, and the required gateway capabilities — sessions_spawn, native-reply session scoping, NO_REPLY — are confirmed). If a capability is unmet, fail closed: do not create routes that would post duplicates or bleed cross-thread context.
2. The staff roles to connect exist in config.staff[] and each has a dual-runtime subagent (.claude/agents/<id>.md + .codex/agents/<id>.toml). If a role or its subagent is missing:
   • Claude Code: run /lisa:add-role <Role> first.
   • Codex: invoke $lisa-wiki:lisa-wiki-add-role first. Only auto-delegate if that skill is available in the active runtime; otherwise print the exact next step and stop. Never infer agent ids from display names — always use config.staff[].id.

Platform selection (identical in both runtimes)

Resolve the platform with this precedence:

1. An explicit platform in the user's request (the Claude commands pre-state telegram or slack).
2. openclaw.defaultPlatform from .lisa.config.json.
3. If still unknown, ask exactly one question: Connect staff via telegram or slack?

Hub-and-spoke contract (both platforms)

• Humans speak only to the facilitator; specialists never take direct human work.
• The facilitator consults specialists via internal OpenClaw sessions_spawn with explicit agentIds — never by messaging another bot on the chat platform (bot-to-bot delivery is unreliable; treat any visible specialist "workroom" as an audit copy, not proof of delivery).
• Each visible human request thread is its own short-term session boundary.
• The facilitator acknowledges after starting consultation, waits/yields for specialist results, evaluates them (asking follow-ups when weak/incomplete/conflicting), synthesizes one answer, and replies in the original thread / native reply.
• After any explicit message-tool send, the agent returns exactly NO_REPLY as its assistant final so the gateway does not post a duplicate loose message.
• Do not instruct agents to add bracketed self-labels like [Facilitator]; the platform shows identity.

Required inputs

• platform (resolved above)
• facilitator: staff id, display name, title, human-facing surface name
• specialists: list of staff ids + roles to attach to this facilitator
• surface visibility: Slack channel private (default) or public; for Telegram, whether any specialist audit topics are wanted (default: none)
• visible bot/app identities (display names, usernames/handles) if separate avatars are needed
• communication rules (who may talk to whom)

For exact route shapes and the facilitator/specialist prompt text, read references/platform-routing.md and references/prompts.md.

Workflow

1. Inspect existing state

Read only what you need; never print token contents:

• ~/.openclaw/openclaw.json (existing agents, channels, groups, topics, routes)
• config.staff[] and the staff subagent files
• existing chat surfaces, apps, and bot accounts (reuse before creating)

2. Plan the platform shape

Telegram: create or reuse one organization supergroup with forum topics enabled; create one human-facing facilitator topic; create one bot per visible identity only when separate names/avatars are needed; specialist audit topics only if explicitly requested. The Bot API chat_id for a supergroup is the signed id (usually starting -100); the topic id is the message_thread_id.

Slack: use Socket Mode for a workstation-hosted gateway unless told otherwise; create or reuse one human-facing facilitator channel (default <organization-slug>-chief-of-staff, private/invite-only unless public is requested); bind routes by stable channel id, not channel name; optional specialist workrooms are audit-only.

Telegram bot-to-bot and bot-originated-topic messages can fail to wake other bots — this is exactly why internal sessions_spawn is the default route.

3. Register apps / bots and store tokens

• Telegram: create bots with the agreed names/usernames; add visible bots to the supergroup, promote as needed, and disable privacy mode when topic messages must reach them.
• Slack: create or reuse the org app; grant only required scopes; save xoxb/xapp tokens.
• Store every token via the configured secret provider (or 0600 local files outside the repo). Never print/paste tokens into chat, logs, docs, or any committed file. After saving, verify the token via an OpenClaw probe or platform API check without exposing it.
• If creation is rate-limited (e.g. BotFather) or needs a human confirmation step, wire what completed, record what is pending plus the retry time, and ask only for the specific approval/code needed.

4. Create or update agent files

For the facilitator and each specialist, ensure the OpenClaw agent exists and its prompt encodes the hub-and-spoke contract. Use the prompt templates in references/prompts.md. The facilitator prompt must require: consult ≥1 specialist before substantive answers; treat the current thread/native-reply root as the session boundary; route via sessions_spawn with explicit agentIds; acknowledge → yield/wait → evaluate → synthesize → reply in the original thread; return NO_REPLY after any message-tool send; isolate/clear/archive consulted specialist context after the investigation. Specialist prompts must require: accept work only via internal dispatch; return concise structured results; never post to human-facing surfaces.

5. Wire OpenClaw routing

Edit ~/.openclaw/openclaw.json carefully (see references/platform-routing.md for exact shapes). Back up the file first. Parse JSON, change only the intended keys, and preserve all unrelated agents, channels, routes, and tokens:

• add/update each agent in agents.list
• give the facilitator subagents.allowAgents = the specialist ids; set subagents.requireAgentId = true when supported
• bind the human-facing surface (Telegram topic / Slack channel) to the facilitator
• bind optional audit surfaces as visibility-only
• for Slack, set channels.slack.replyToModeByChatType.channel = "all" so acknowledgements and final answers are real thread replies
• disable any default-bot fallback that would answer instead of the facilitator

Show the exact route keys you will change before writing.

6. Validate

Run, waiting for the gateway to warm up before declaring success:

openclaw config validate
openclaw gateway restart
openclaw channels status --probe --timeout 90000

7. Reset stale sessions (when changing an existing route's behavior)

Archive (don't delete) affected session files under ~/.openclaw/session-archive/, remove active session pointers for the changed routes, restart the gateway, and re-probe. Old session history can preserve stale routing instructions after a prompt/config change.

8. End-to-end route test

Do not call the work complete until the live loop passes. Acceptance criteria:

1. A human post reaches the facilitator surface.
2. The facilitator acknowledges as a thread reply / native reply to the original message.
3. A second post in the same channel/topic but a different visible thread gets a distinct session context (no cross-thread bleed).
4. The facilitator starts internal sessions_spawn consultation with ≥1 explicit specialist id.
5. A specialist returns an internal result.
6. The facilitator evaluates and asks a follow-up if needed.
7. The facilitator synthesizes and replies in the original thread / native reply.
8. No duplicate loose message appears after the message-tool send (the NO_REPLY rule held).

If the test fails, inspect gateway logs and sessions before changing config; check the bot's admin rights (Telegram) / app channel membership and scopes (Slack), and mention-gating, first.

Output standard

Finish with: platform and human-facing surface; surfaces created/reused; apps/bots registered and any pending; token storage location (no values); facilitator + specialist agents created/updated; validation results; end-to-end test result; and any remaining manual or cooldown follow-up.

Related

lisa-openclaw-setup (run first), lisa-openclaw-connect-repo-topic (Telegram repo-coding topics). Staff "brains" come from the lisa-wiki plugin's add-role.