How do I install the Channel Bot skill?

Run npx skillmds@latest add vstorm-co/channel-bot-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Channel Bot safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Channel Bot?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Channel Bot free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Channel Bot?

vstorm-co (@vstorm-co) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Channel Bot by vstorm-co — Agent Skill

Name: Channel Bot
Author: vstorm-co

Channel Bot

Work with messaging-channel bots (Telegram / Slack) — register a bot, route inbound messages through the AI agent, handle webhooks vs polling, or add a new channel adapter. Use when wiring chat into a messaging platform or debugging bot delivery.

vstorm-co Updated Sep 22, 2026

File contents

Messaging Channels (Telegram / Slack)

Channels are a thick service at backend/app/services/channels/: per-platform adapters plus a router that funnels inbound messages into the same agent pipeline as the web chat.

Layout

File	Responsibility
`base.py`	Shared channel adapter interface
`telegram.py`	Telegram adapter (aiogram v3)
`slack.py`	Slack adapter (Events API + Socket Mode)
`router.py`	Maps an inbound platform message → conversation/session → agent run → reply
`chart_render.py`	Renders chart tool output as PNG for channels

Bots are stored in the DB (channel_bot), with per-user identity (channel_identity) and per-thread session (channel_session) tables. Bot tokens are encrypted at rest with CHANNEL_ENCRYPTION_KEY (Fernet).

Register / manage a bot

uv run {{ cookiecutter.project_slug }} cmd channel ...   # see `cmd channel --help`

Webhook vs polling

Polling (dev): the adapter long-polls the platform — no public URL needed.
Webhook (prod): the platform POSTs to POST /api/v1/telegram/{bot_id}/webhook / the Slack events endpoint. Verify the signature/secret (HMAC for Telegram, signing secret for Slack) before processing.

Add a new channel adapter

Implement an adapter in services/channels/<platform>.py against the base.py interface (parse inbound → normalized message; send outbound).
Wire it into router.py so inbound messages reach the agent and replies stream back.
Add a webhook route under api/routes/v1/ (signature-verified) and/or a polling entrypoint.
Reuse the existing conversation/session model — don't fork the agent pipeline.

Rules

Inbound messages flow through router.py into the same agent/session pipeline as web chat — don't duplicate agent logic per platform.
Always verify webhook signatures before acting on a payload.
Store tokens encrypted (CHANNEL_ENCRYPTION_KEY); never log or echo them.
Respect per-group/per-thread concurrency controls already in the adapters.

---name: channel-bot-2description: Work with messaging-channel bots (Telegram / Slack) — register a bot, route inbound messages through the AI agent, handle webhooks vs polling, or add a new channel adapter. Use when wiring chat into a messaging platform or debugging bot delivery.---# Messaging Channels (Telegram / Slack)Channels are a **thick service** at `backend/app/services/channels/`: per-platform adapters plus a router that funnels inbound messages into the **same agent pipeline** as the web chat.## Layout| File | Responsibility ||------|---------------|| `base.py` | Shared channel adapter interface || `telegram.py` | Telegram adapter (aiogram v3) || `slack.py` | Slack adapter (Events API + Socket Mode) || `router.py` | Maps an inbound platform message → conversation/session → agent run → reply || `chart_render.py` | Renders chart tool output as PNG for channels |Bots are stored in the DB (`channel_bot`), with per-user identity (`channel_identity`) and per-thread session (`channel_session`) tables. Bot tokens are encrypted at rest with `CHANNEL_ENCRYPTION_KEY` (Fernet).## Register / manage a bot```bashuv run {{ cookiecutter.project_slug }} cmd channel ... # see `cmd channel --help````## Webhook vs polling- **Polling (dev):** the adapter long-polls the platform — no public URL needed.- **Webhook (prod):** the platform POSTs to `POST /api/v1/telegram/{bot_id}/webhook` / the Slack events endpoint. Verify the signature/secret (HMAC for Telegram, signing secret for Slack) before processing.## Add a new channel adapter1. Implement an adapter in `services/channels/<platform>.py` against the `base.py` interface (parse inbound → normalized message; send outbound).2. Wire it into `router.py` so inbound messages reach the agent and replies stream back.3. Add a webhook route under `api/routes/v1/` (signature-verified) and/or a polling entrypoint.4. Reuse the existing conversation/session model — don't fork the agent pipeline.## Rules- Inbound messages flow through `router.py` into the **same** agent/session pipeline as web chat — don't duplicate agent logic per platform.- Always verify webhook signatures before acting on a payload.- Store tokens encrypted (`CHANNEL_ENCRYPTION_KEY`); never log or echo them.- Respect per-group/per-thread concurrency controls already in the adapters.

Frequently asked questions