qwen-prompting

qwen-prompting is a skill for Claude Code from josephyaduvanshi/qwen-companion. It costs 37 tokens per session (1,060 once invoked), scanned A, original, Apache-2.0.

A command that checks whether the local Qwen Code command-line tool is installed and ready, with an optional setting for a stop-time review check. Qwen Code is a separate coding agent that can be used alongside Claude Code.

In plain words
What is it for?
Use it to verify Qwen Code setup, optionally install it through npm when available, and enable or disable the repository's review gate.
Why use it?
It shows whether Qwen can be used before another command depends on it, and reports authentication or installation steps when needed. It can also turn the review check on or off for a repository.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions Claude Code.

Part of the qwen plugin — 3 skills, 7 commands, 1 agent, 3 hooks shipped together

Good fit Use it to verify Qwen Code setup, optionally install it through npm when available, and enable or disable the repository's review gate.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/josephyaduvanshi/qwen-companion/qwen-prompting
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 josephyaduvanshi/qwen-companion --skill qwen-prompting
Clone the repo
git clone --depth 1 https://github.com/josephyaduvanshi/qwen-companion

Made for: Claude Code.

Or install qwen, the plugin that ships this one along with the rest of its 3 skills, 7 commands, 1 agent, 3 hooks.

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 qwen-prompting

README.md
[![agentmods](https://agentmods.dev/badge/skills/josephyaduvanshi/qwen-companion/qwen-prompting/github.svg)](https://agentmods.dev/skills/josephyaduvanshi/qwen-companion/qwen-prompting)
Your own site
<a href="https://agentmods.dev/skills/josephyaduvanshi/qwen-companion/qwen-prompting"><img src="https://agentmods.dev/badge/skills/josephyaduvanshi/qwen-companion/qwen-prompting/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 qwen-prompting

Your own site · 80×15
<a href="https://agentmods.dev/skills/josephyaduvanshi/qwen-companion/qwen-prompting"><img src="https://agentmods.dev/badge/skills/josephyaduvanshi/qwen-companion/qwen-prompting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,060 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.
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 $0.00037 $0.01060
Opus 5 $0.00018 $0.00530
Sonnet 5 $0.00007 $0.00212
Haiku 4.5 $0.00004 $0.00106

Measured 12d ago against content hash 52cb0e44300c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qwen-prompting 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.

plugins/qwen/skills/qwen-prompting/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Qwen Prompting

Use this skill when qwen:qwen-rescue needs to ask Qwen Code for help.

Prompt Qwen like an operator, not a collaborator. Keep prompts compact and block-structured with XML tags. State the task, the output contract, the follow-through defaults, and the small set of extra constraints that matter.

Core rules:

  • Prefer one clear task per Qwen run. Split unrelated asks into separate runs.
  • Tell Qwen what done looks like. Do not assume it will infer the desired end state.
  • Add explicit grounding and verification rules for any task where unsupported guesses would hurt quality.
  • Prefer better prompt contracts over raising reasoning or adding long natural-language explanations.
  • Use XML tags consistently so the prompt has stable internal structure.
  • Qwen Code's default models (qwen3.5-plus, qwen3-max, qwen3-coder-plus) are strong at code edits and tool use but prefer explicit contracts. Spell out file boundaries, acceptance criteria, and stop conditions.

Default prompt recipe:

  • <task>: the concrete job and the relevant repository or failure context.
  • <structured_output_contract> or <compact_output_contract>: exact shape, ordering, and brevity requirements.
  • <default_follow_through_policy>: what Qwen should do by default instead of asking routine questions.
  • <verification_loop> or <completeness_contract>: required for debugging, implementation, or risky fixes.
  • <grounding_rules> or <citation_rules>: required for review, research, or anything that could drift into unsupported claims.

When to add blocks:

  • Coding or debugging: add completeness_contract, verification_loop, and missing_context_gating.
  • Review or adversarial review: add grounding_rules, structured_output_contract, and dig_deeper_nudge.
  • Research or recommendation tasks: add research_mode and citation_rules.
  • Write-capable tasks: add action_safety so Qwen stays narrow and avoids unrelated refactors.

How to choose prompt shape:

  • There is no dedicated review/adversarial-review command in v0.1 of this plugin. For review-style work, send a task prompt with a <task>Review ...</task> block plus a strict <structured_output_contract>.
  • Use task when the task is diagnosis, planning, research, or implementation and you need to control the prompt directly.

Working rules:

  • Prefer explicit prompt contracts over vague nudges.
  • Use stable XML tag names.
  • Do not raise reasoning or complexity first. Tighten the prompt and verification rules before escalating.
  • Ask Qwen for brief, outcome-based progress updates only when the task is long-running or tool-heavy.
  • Keep claims anchored to observed evidence. If something is a hypothesis, say so.

Prompt assembly checklist:

  1. Define the exact task and scope in <task>.
  2. Choose the smallest output contract that still makes the answer easy to use.
  3. Decide whether Qwen should keep going by default or stop for missing high-risk details.
  4. Add verification, grounding, and safety tags only where the task needs them.
  5. Remove redundant instructions before sending the prompt.

Read the full file on GitHub · 94 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 · 94 lines · 37 tokens per session scan A 52cb0e44300c

Subscribe to this mod's changes

qwen-prompting is a skill published in the GitHub repository josephyaduvanshi/qwen-companion (11 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,060 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.

Related

Other skills, from other repositories

llm-app-patterns

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

davila7/claude-code-templates · 54 tokens

prompt-optimization

Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…

langwatch/langwatch · 105 tokens

enhance-prompt

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

google-labs-code/stitch-skills · 41 tokens

prompt-engineer

Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot…

Jeffallan/claude-skills · 93 tokens

seedance-vocab-en

This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.

Emily2040/seedance-2.0 · 61 tokens

ideogram4

Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers…

digitalsamba/claude-code-video-toolkit · 99 tokens