QwenPaw is a personal AI assistant that runs on a local machine or in the cloud and connects to multiple chat applications. It provides memory, file workspaces, multiple agents, skills, plugins, and integrations with language-model providers and external tools. The catalogue entries are skills that extend its capabilities.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agentscope-ai/QwenPaw --skill channel_message-engit clone --depth 1 https://github.com/agentscope-ai/QwenPawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentscope-ai/qwenpaw/channel_message-en)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/channel_message-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/channel_message-en/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/channel_message-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/channel_message-en.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01518 |
| Opus 5 | $0.00029 | $0.00759 |
| Sonnet 5 | $0.00012 | $0.00304 |
| Haiku 4.5 | $0.00006 | $0.00152 |
Grade A, and why
channel_message scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- channel_message — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Channel Message
When to Use
Use this skill only when the user explicitly asks you to send a message to a channel/session, or when you need to proactively push a notification (e.g., task completion, reminders, alerts). This is a one-way send — no reply is returned.
Should Use
- The user explicitly asks to send to a specific channel/session
- Proactively notifying the user after a task completes
- Scheduled reminders, alerts, or status updates
- Pushing async results back to an existing session
- The user explicitly says "notify me when done"
Should Not Use
- If you are simply replying in the current session, do not use
qwenpaw channels send - You need a two-way conversation and expect an immediate reply
- You do not know which target session to use
- You are guessing
target-userortarget-session
Decision Rules
- Only use this when the user explicitly asks to send to a channel/session, or proactive notification is needed
- You must query sessions before sending
- Do not guess
target-userortarget-session - If multiple sessions are found, prefer the most recently active one
channel sendis a one-way push — no user reply is returned
Most Common Commands
1) Query available sessions first
qwenpaw chats list --agent-id <your_agent> --channel <channel>
You can also filter by user:
qwenpaw chats list --agent-id <your_agent> --user-id <user_id>
2) Send a message
qwenpaw channels send \
--agent-id <your_agent> \
--channel <channel> \
--target-user <user_id> \
--target-session <session_id> \
--text "..."
Minimal Workflow
1. Determine: is the user explicitly requesting a send, or is proactive notification needed?
2. qwenpaw chats list — query the target session
3. Extract user_id and session_id from the results
4. If multiple sessions exist, prefer the most recently active one
5. qwenpaw channels send — send the message
6. Done (no reply)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 251 lines · 58 tokens per session scan A ff5f85d79ed1
channel_message is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,741 stars, last pushed yesterday), licensed Apache-2.0. It adds 58 tokens to every session and 1,518 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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