guidance

guidance is a skill for Claude Code, Codex from agentscope-ai/QwenPaw. It costs 44 tokens per session (1,382 once invoked), scanned A, original, Apache-2.0.

A guide for answering questions about installing and configuring QwenPaw, a software tool with local documentation. It says to check those documents first and use official website information only when needed.

In plain words
What is it for?
Explaining setup, initialization, environment configuration, required software, and common QwenPaw settings.
Why use it?
It reduces guesswork about installation steps, dependencies, and configuration settings. Answers are based on available documentation and use the same language as the question.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for qwenpaw. Also seen: positional $N argument; built for qwenpaw.

Good fit Explaining setup, initialization, environment configuration, required software, and common QwenPaw settings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentscope-ai/qwenpaw/guidance-zh
About the project

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.

agentscope-ai/QwenPaw · 34,809 stars · on GitHub · qwenpaw.agentscope.io

Install

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.

Any agent
npx skills add agentscope-ai/QwenPaw --skill guidance-zh
Clone the repo
git clone --depth 1 https://github.com/agentscope-ai/QwenPaw

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for guidance

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/guidance-zh/github.svg)](https://agentmods.dev/skills/agentscope-ai/qwenpaw/guidance-zh)
Your own site
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/guidance-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/guidance-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.

agentmods 80×15 button for guidance

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/guidance-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/guidance-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,382 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.01382
Opus 5 $0.00022 $0.00691
Sonnet 5 $0.00009 $0.00276
Haiku 4.5 $0.00004 $0.00138

Measured 12d ago against content hash f6fc7f104e60, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

guidance 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • guidance — 95% identical, 34 lines differ
src/qwenpaw/agents/skills/guidance-zh/SKILL.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QwenPaw 安装与配置问答指南

当用户询问 QwenPaw 的安装、初始化、环境配置、依赖要求、常见配置项 时,使用本 skill。

核心原则:

  • 先查本地文档,再回答
  • 回答要基于已读到的内容,不臆测
  • 回答语言与用户提问语言保持一致

标准流程

第一步:定位文档位置

优先使用内置路径解析(适用于所有安装方式)

DOCS_DIR=$(python3 -c "from qwenpaw.constant import DOCS_DIR; print(DOCS_DIR or '')" 2>/dev/null)

如果上面获取到了非空路径且目录存在,直接使用,跳到第二步。

如果获取失败(例如旧版本未包含 DOCS_DIR),按以下顺序 fallback:

查找记忆中的文档目录

首先你可以查看memory中是否有文档目录,如果有则直接使用,如果没有则继续执行下一步。

# 获取memory中的文档目录
DOCS_DIR=$(find ~/.qwenpaw/memory/ -type d -name "docs")

如果 memory 中没有文档目录,则继续执行下面的逻辑。

检查项目源码中的文档目录

执行以下脚本逻辑来获取变量 $QWENPAW_ROOT:

# 获取二进制绝对路径
QWENPAW_PATH=$(which qwenpaw 2>/dev/null || whereis qwenpaw | awk '{print $2}')

# 逻辑推导:如果路径包含 .qwenpaw/bin/qwenpaw,则根目录在其上三层
# 例如:/path/to/QwenPaw/.qwenpaw/bin/qwenpaw -> /path/to/QwenPaw
if [[ "$QWENPAW_PATH" == *".qwenpaw/bin/qwenpaw" ]]; then
    QWENPAW_ROOT=$(echo "$QWENPAW_PATH" | sed 's/\/\.qwenpaw\/bin\/qwenpaw//')
else
    # 兜底:尝试获取所在目录的父目录
    QWENPAW_ROOT=$(dirname $(dirname "$QWENPAW_PATH") 2>/dev/null || echo ".")
fi

echo "Detected QwenPaw Root: $QWENPAW_ROOT"

验证并列出文档目录: 使用推导出的 $QWENPAW_ROOT 定位文档:

# 组合标准文档路径
DOCS_DIR="$QWENPAW_ROOT/website/public/docs/"

# 检查路径是否存在并列出文件
if [ -d "$DOCS_DIR" ]; then
    find "$DOCS_DIR" -type f -name "*.md" | head -n 100
else
    # 如果推导路径不对,执行全局模糊搜索
    find "$QWENPAW_ROOT" -type d -name "docs" | grep "website/public/docs"
fi

如果项目文档不存在,搜索工作目录

如果还是找不到文档,搜索 qwenpaw 安装路径下的可用文档内容:

# 寻找 faq.en.md 或 config.zh.md 等特征文件
FILE_PATH=$(find . -type f -name "faq.en.md" -o -name "config.zh.md" | head -n 1)
if [ -n "$FILE_PATH" ]; then
    # 使用 dirname 获取该文件所在的目录
    DOCS_DIR=$(dirname "$FILE_PATH")
fi

如果找到了文档目录,请你记录在 memory 中,格式为:

# 文档目录
$DOCS_DIR = <doc_path>

第二步:文档检索与匹配

文档文件命名格式为 <topic>.<lang>.md(如 config.zh.mdconfig.en.mdquickstart.zh.md)。

使用 find 命令在目标目录中列出所有符合后缀的文档,并根据文件名关键字(如 install, env, setup)锁定目标作为 <doc_path>。

# 列出所有符合后缀的文档
find $DOCS_DIR -type f -name "*.md"

Read the full file on GitHub · 148 lines

Changes

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.

  1. 12d ago First seen · 148 lines · 44 tokens per session scan A f6fc7f104e60

Subscribe to this mod's changes

guidance is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,809 stars, last pushed today), licensed Apache-2.0. It adds 44 tokens to every session and 1,382 once invoked, about $0.0002 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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