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 make-skill-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/make-skill-en)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/make-skill-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/make-skill-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/make-skill-en"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/make-skill-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 | $0.00060 | $0.01506 |
| Opus 5 | $0.00030 | $0.00753 |
| Sonnet 5 | $0.00012 | $0.00301 |
| Haiku 4.5 | $0.00006 | $0.00151 |
Grade A, and why
make-skill 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Make Skill
Create one new workspace Skill from the raw current conversation. Use the scripts in this directory for the lifecycle below; do not rely on a make-skill-specific core tool, mode, or state store.
Run each documented python scripts/... command through execute_shell_command, setting cwd to this Skill's <dir> from the available-skills entry; every script reads one JSON object from stdin (or --input <file>) and writes one JSON object to stdout.
Plan
The focus in /make-skill <focus> is required. For a natural-language request, infer it from the request and current conversation. Later user corrections replace conflicting earlier rules. Preserve stable guidance, contracts, templates, and workflows that should change future behavior; exclude one-off data, temporary paths, secrets, and retry chatter.
Read primary type and package, then choose one primary type and only the files it needs. When the proposed test mode is not off, read behavior testing before defining its target.
Batch workflows
A stored batch is a parameterized run_tool_batch program bundled with a workflow Skill. Use batch: true when a reusable region's actions, branches, and success condition can be stated before execution and one stored entrypoint saves meaningful agent-tool round trips. The region may be the whole workflow, one substantial helper, or one semantic tool-native action; action count is not the criterion. Runtime data, observations, and a final agent review do not prevent batching when the rule for handling them is already known.
Use batch: false only when execution must invent the next action or success condition at runtime, or a shared entrypoint has no practical reuse value. If the user explicitly requests Batch, treat it as an approved plan refinement and revise the plan without reopening eligibility.
Only after selecting batch: true, read run batch before finalizing the workflow and file tree. When batch: false, do not read it.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed · -618 lines · -25 tokens per session f269e951f0fc
- 10d ago First seen · 724 lines · 85 tokens per session scan A 6f6c153131cb
make-skill is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,741 stars, last pushed today), licensed Apache-2.0. It adds 60 tokens to every session and 1,506 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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