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-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/qa_source_index-en)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/qa_source_index-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/qa_source_index-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/qa_source_index-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/qa_source_index-en.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 | $0.00065 | $0.01094 |
| Opus 5 | $0.00032 | $0.00547 |
| Sonnet 5 | $0.00013 | $0.00219 |
| Haiku 4.5 | $0.00006 | $0.00109 |
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 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:
- QA_source_index — 89% 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.
Documentation and Source Code Quick Reference
When answering questions about installation, configuration, or behavioral principles, first classify by keyword, then open 1–2 paths most likely to contain the answer from the table below, avoiding aimless directory traversal.
Usage Steps
- Extract the topic from the user's question (match against the left column or synonyms in the table below).
- Resolve
$QWENPAW_ROOT: usewhich qwenpawto get the executable path. If it is…/.qwenpaw/bin/qwenpaw, the source root is three levels up (consistent with the guidance skill); otherwise, determine it from the user-provided installation path. - Resolve
$DOCS_DIRfirst (cross-install compatible): runpython3 -c "from qwenpaw.constant import DOCS_DIR; print(DOCS_DIR or '')" 2>/dev/null. If it returns a valid path, use it directly. Otherwise, fallback to$QWENPAW_ROOT/website/public/docs/. - Read documentation first:
$DOCS_DIR/<topic>.<language>.md(use the same language as the user:zh/en.). If that is insufficient, read the source entry points listed in the table.
Topic / Keywords → Preferred Documentation and Source Code
| Topic or Keywords (examples) | Preferred Documentation ($DOCS_DIR/) |
Common Source Entry Points (relative to $QWENPAW_ROOT) |
|---|---|---|
| Installation, dependencies, getting started | quickstart, intro |
src/qwenpaw/cli/, pyproject.toml |
| Configuration, config.json, environment variables | config |
src/qwenpaw/config/config.py, src/qwenpaw/constant.py |
| Skills, SKILL, skill_pool, built-in skills | skills |
src/qwenpaw/agents/skill_system/, src/qwenpaw/agents/skills/ |
| MCP, plugins | mcp |
src/qwenpaw/app/routers/ (grep mcp as needed) |
| Multi-agent, workspace, agent, built-in QA | multi-agent |
src/qwenpaw/app/routers/agents.py, src/qwenpaw/app/migration.py, src/qwenpaw/constant.py (BUILTIN_QA_AGENT_ID, etc.) |
| Memory, MEMORY, memory_search | memory |
src/qwenpaw/agents/memory/memory_manager.py, src/qwenpaw/agents/tools/memory_search.py |
| Console, frontend | console |
console/ |
| CLI, subcommands, init | cli |
src/qwenpaw/cli/ (e.g., init_cmd.py) |
| Channels, sessions | channels |
Search for channels keyword under src/qwenpaw |
| Context, window | context |
config docs + related logic in src/qwenpaw/agents/ |
| Models, API Key | models |
src/qwenpaw/config/config.py |
| Heartbeat, HEARTBEAT | heartbeat |
Search for heartbeat / HEARTBEAT under src/qwenpaw |
| Desktop client | desktop |
desktop/ (if present in the repository) |
| Security | security |
Read security.<lang>.md first |
| Errors, FAQ | faq |
Read faq.<lang>.md first, then examine source code as needed |
| Commands and slash commands | commands |
CLI/command registration modules under src/qwenpaw (search as needed) |
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 · 52 lines · 65 tokens per session scan A da0b9d22e29b
QA_source_index is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,741 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 1,094 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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