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 qa_source_index-zhgit 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/qa_source_index-zh)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/qa_source_index-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/qa_source_index-zh/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/qa_source_index-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/qa_source_index-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00069 | $0.01157 |
| Opus 5 | $0.00034 | $0.00579 |
| Sonnet 5 | $0.00014 | $0.00231 |
| Haiku 4.5 | $0.00007 | $0.00116 |
Grade A, and why
QA_source_index 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 12d 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:
- QA_source_index — 86% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
文档与源码速查
回答 安装、配置、行为原理 类问题时，先 按关键词归类，再按下表 打开 1～2 个最可能命中的路径 阅读，避免长时间无目的遍历。
使用步骤
- 从用户问题中提取主题（对照下表左列或同类词）。
- 解析
$QWENPAW_ROOT：以which qwenpaw得到可执行路径，若为…/.qwenpaw/bin/qwenpaw则源码根为其上三级目录（与 guidance skill 一致）；否则结合用户给出的安装路径判断。 - 先解析
$DOCS_DIR（兼容多种安装方式）：执行python3 -c "from qwenpaw.constant import DOCS_DIR; print(DOCS_DIR or '')" 2>/dev/null。若返回有效路径则直接使用；否则 fallback 到$QWENPAW_ROOT/website/public/docs/。 - 先读文档
$DOCS_DIR/<专题>.<语言>.md（语言取与用户一致：zh/en），仍不足再读表中 源码入口。
主题 / 关键词 → 优先文档与源码
| 主题或关键词（示例） | 优先文档（$DOCS_DIR/） |
常见源码入口（相对 $QWENPAW_ROOT） |
|---|---|---|
| 安装、依赖、首次使用 | quickstart、intro |
src/qwenpaw/cli/、pyproject.toml |
| 配置、config.json、环境变量 | config |
src/qwenpaw/config/config.py、src/qwenpaw/constant.py |
| 技能、SKILL、skill_pool、内置技能 | skills |
src/qwenpaw/agents/skill_system/、src/qwenpaw/agents/skills/ |
| MCP、插件 | mcp |
src/qwenpaw/app/routers/（按需 grep mcp） |
| 多智能体、工作区、agent、内置 QA | multi-agent |
src/qwenpaw/app/routers/agents.py、src/qwenpaw/app/migration.py、src/qwenpaw/constant.py（BUILTIN_QA_AGENT_ID 等） |
| 记忆、MEMORY、memory_search | memory |
src/qwenpaw/agents/memory/memory_manager.py、src/qwenpaw/agents/tools/memory_search.py |
| 控制台、前端 | console |
console/ |
| 命令行、子命令、init | cli |
src/qwenpaw/cli/（如 init_cmd.py） |
| 频道、会话 | channels |
在 src/qwenpaw 下按 channels 关键词检索 |
| 上下文、窗口 | context |
config 文档 + src/qwenpaw/agents/ 相关逻辑 |
| 模型、API Key | models |
src/qwenpaw/config/config.py |
| 心跳、HEARTBEAT | heartbeat |
在 src/qwenpaw 下检索 heartbeat / HEARTBEAT |
| 桌面客户端 | desktop |
desktop/（若仓库中存在） |
| 安全 | security |
先读 security.<lang>.md |
| 报错、常见问题 | faq |
先 faq.<lang>.md，再针对性看源码 |
| 命令与斜杠指令 | commands |
src/qwenpaw 下与 CLI/命令注册相关的模块（按需检索） |
约定
- 文档完整路径：
$DOCS_DIR/<专题>.<语言>.md（无对应语言时用.en.md兜底）。优先使用qwenpaw.constant中的DOCS_DIR，失败时 fallback 到$QWENPAW_ROOT/website/public/docs/。 - 表中 源码入口 为起点；应用
read_file或局部grep缩小到具体符号，不要一次性通读大目录 listing。
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.
- 12d ago First seen · 52 lines · 69 tokens per session scan A b0ca4aa779b7
QA_source_index is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,809 stars, last pushed today), licensed Apache-2.0. It adds 69 tokens to every session and 1,157 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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