Process Inbox
telegramdesktop/tdesktop
Process the local ignored ai-tdesktop inbox into durable, independently testable Telegram Desktop task records while task execution worktrees remain active.
A skill your agent uses when running QA Lab channel message flow evidence.
$ npx skills add openclaw/openclaw --skill channel-message-flows -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openclaw/openclaw channel-message-flows --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/channel-message-flows .claude/skills/channel-message-flows && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .claude/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flowsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openclaw/openclaw --skill channel-message-flows -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openclaw/openclaw channel-message-flows --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/channel-message-flows .agents/skills/channel-message-flows && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .agents/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/openclaw --skill channel-message-flows -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openclaw/openclaw channel-message-flows --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/channel-message-flows .cursor/skills/channel-message-flows && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .cursor/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openclaw/openclaw.git --path .agents/skills/channel-message-flows--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openclaw/openclaw --skill channel-message-flows -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openclaw/openclaw channel-message-flows --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/channel-message-flows .gemini/skills/channel-message-flows && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .gemini/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openclaw/openclaw channel-message-flowsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openclaw/openclaw --skill channel-message-flows -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/channel-message-flows .github/skills/channel-message-flows && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .github/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openclaw/openclaw --skill channel-message-flows -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openclaw/openclaw channel-message-flows --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openclaw/openclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/channel-message-flows .opencode/skills/channel-message-flows && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "channel-message-flows" agent skill from https://github.com/openclaw/openclaw/tree/main/.agents/skills/channel-message-flows into .opencode/skills/channel-message-flows/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "channel-message-flows", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
channel-message-flowsA skill your agent uses when running QA Lab channel message flow evidence.
Channel Message Flows is an agent skill from openclaw/openclaw. Use when running QA Lab channel message flow evidence.
Its SKILL.md is about 310 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with Telegram. The repository describes itself as: The AI that really does things. Any OS. Any Platform. The lobster way. 🦞. The licence is MIT.
Read from SKILL.md and the folder at commit 1eb5970. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
nodeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Channel Message Flows loads about 306 tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 79 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from openclaw/openclaw at commit 1eb5970, republished under its MIT licence (© openclaw). 79 words, ~306 tokens.
.claude/skills/channel-message-flows/SKILL.md (or your agent's skills folder).Use this from the OpenClaw repo root to run the QA Lab evidence for Telegram draft/final delivery sequencing. The behavior is owned by one transport-native QA flow that can run through QA Channel or Crabline Telegram.
Run the scenario through QA Lab:
OPENCLAW_BUILD_PRIVATE_QA=1 node scripts/run-node.mjs qa suite \
--provider-mode mock-openai \
--scenario channel-message-flows \
--channel-driver qa-channelRun the same YAML through the real Telegram plugin against Crabline's local provider server:
OPENCLAW_BUILD_PRIVATE_QA=1 node scripts/run-node.mjs qa suite \
--provider-mode mock-openai \
--scenario channel-message-flows \
--channel-driver crabline \
--channel telegramqa/scenarios/channels/channel-message-flows.yamlextensions/qa-channel/src/inbound.tsextensions/qa-lab/src/qa-transport.tsextensions/qa-lab/src/crabline-transport.tsextensions/telegram/src/draft-stream.tsThe scenario covers channels.streaming as primary evidence and
runtime.delivery as secondary evidence.
© openclaw, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/channel-message-flows of openclaw/openclaw.
Open the folder on GitHubat commit 1eb5970
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in openclaw/openclaw, which our catalogue first saw on October 8, 2026.
Channel Message Flows next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Channel Message Flows this skillopenclaw/openclaw | 392k | 1 repos | ~306 | Automated safety check: Pass | MIT | |
| Process Inboxtelegramdesktop/tdesktop | 33k | 2 repos | ~4.5k | Automated safety check: Pass | GPL-3.0 | |
| Perform Tasktelegramdesktop/tdesktop | 33k | 2 repos | ~3k | Automated safety check: Pass | GPL-3.0 | |
| Custom Mode Creator for claude-memthedotmack/claude-mem | 98k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Continuetelegramdesktop/tdesktop | 33k | 2 repos | ~9.4k | Automated safety check: Pass | GPL-3.0 | |
| Rebasetelegramdesktop/tdesktop | 33k | 1 repos | ~3.7k | Automated safety check: Pass | GPL-3.0 |
telegramdesktop/tdesktop
Process the local ignored ai-tdesktop inbox into durable, independently testable Telegram Desktop task records while task execution worktrees remain active.
telegramdesktop/tdesktop
Resolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results.
thedotmack/claude-mem
Walks you through creating, installing and verifying a custom claude-mem mode, including note types, tags and optional Telegram alerts for chosen memories.
telegramdesktop/tdesktop
Continue autonomous Telegram Desktop development from the shared ai-tdesktop repository.
telegramdesktop/tdesktop
Drive an intent-aware rebase of the current checkout, resolving every conflict by reading the history behind both sides instead of by making the markers disappear.
op7418/Claude-to-IM-skill
Bridge THIS Claude Code or Codex session to Telegram, Discord, Feishu/Lark, QQ, or WeChat so the user can chat with Claude from their phone.
openclaw/openclaw
Maintain the canonical live OpenClaw main checkout, macOS LaunchAgent-managed Gateway, local macOS app, exact-head main CI, and recurring full release validation.
openclaw/openclaw
Control tmux sessions/panes for interactive CLIs: list, capture output, send keys, paste text, monitor prompts.
openclaw/openclaw
Feishu document read/write workflows. An agent skill from openclaw/openclaw.
openclaw/openclaw
Review, triage, repair, or land OpenClaw issues and pull requests with current-source evidence and the native maintainer workflow.
openclaw/openclaw
A skill your agent uses when controlling web pages with the OpenClaw browser tool, especially multi-step flows, login checks, tab management, or recovery from stale refs/timeouts.
openclaw/openclaw
A skill your agent uses for all ClawSweeper work: OpenClaw issue/PR sweep reports, repair jobs, cloud fix PRs, @clawsweeper maintainer mention commands, trusted ClawSweeper-reviewed…
Works with
A skill your agent uses when running QA Lab channel message flow evidence. Channel Message Flows is an agent skill from openclaw/openclaw. Use when running QA Lab channel message flow evidence.
Channel Message Flows fits situations like: running QA Lab channel message flow evidence.
Run `npx skills add openclaw/openclaw --skill channel-message-flows -a claude-code`. Or copy the skill folder (.agents/skills/channel-message-flows in openclaw/openclaw) into .claude/skills/channel-message-flows in your project. Claude Code loads it when a task matches its description.
Run `npx skills add openclaw/openclaw --skill channel-message-flows -a codex`. Or copy the skill folder (.agents/skills/channel-message-flows in openclaw/openclaw) into .agents/skills/channel-message-flows in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openclaw/openclaw --skill channel-message-flows -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/channel-message-flows, .gemini/skills/channel-message-flows, .github/skills/channel-message-flows and .opencode/skills/channel-message-flows in your project.
Going by SKILL.md and its folder, Channel Message Flows needs the command-line tools its instructions call (node).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Channel Message Flows is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 306 tokens (SKILL.md is roughly 1.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Channel Message Flows: Process Inbox (telegramdesktop/tdesktop, 33k stars), Perform Task (telegramdesktop/tdesktop, 33k stars), Custom Mode Creator for claude-mem (thedotmack/claude-mem, 98k stars) and Continue (telegramdesktop/tdesktop, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
openclaw (a GitHub organization) maintains it in openclaw/openclaw, which has 391,610 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 8, 2026.
Source: openclaw/openclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.