Qwen Delegation Skill for Claude
Delegates tasks to Qwen CLI via delegation-core for Alibaba's models. Use when delegation-core selects Qwen or large-context batch processing is needed.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/athola/claude-night-market --skill qwen-delegationThe instruction itself
13 sections, as written by the authorTable of Contents
- Overview
- When to Use
- Prerequisites
- Quick Start
- Smart Delegation
- Qwen-Specific Details
Qwen CLI Delegation
Overview
This skill implements conjure:delegation-core for the Qwen CLI.
It provides Qwen-specific authentication, quota management,
and command construction.
For shared delegation patterns, see Skill(conjure:delegation-core).
When To Use
- After
Skill(conjure:delegation-core)determines Qwen is suitable - When you need Qwen's large context window (100K+ tokens)
- For batch processing, summarization, or multi-file analysis
- If the
qwenCLI is installed and configured
When NOT To Use
- Choosing which provider to delegate to (use
conjure:delegation-core) - Gemini was the selected provider (use
conjure:gemini-delegation)
Prerequisites
Installation:
# Install Qwen CLI
pip install qwen-cli
# Verify installation
qwen --version
# Check authentication
qwen auth status
# Login if needed
qwen auth login
# Or set API key
export QWEN_API_KEY="your-key"
Verification: Run python --version to verify Python environment.
Quick Start
Using Shared Delegation Executor
# Basic file analysis
python ~/conjure/tools/delegation_executor.py qwen "Analyze this code" --files src/main.py
# With specific model
python ~/conjure/tools/delegation_executor.py qwen "Summarize" --files src/**/*.py --model qwen-max
# With output format
python ~/conjure/tools/delegation_executor.py qwen "Extract functions" --files src/main.py --format json
Direct CLI Usage
# Basic command
qwen -p "@path/to/file Analyze this code"
# Multiple files
qwen -p "@src/**/*.py Summarize these files"
# Specific model
qwen --model qwen-max -p "..."
Save Output
qwen -p "..." > delegations/qwen/$(date +%Y%m%d_%H%M%S).md
Smart Delegation
The shared delegation executor can auto-select the best service:
# Auto-select based on requirements
python ~/conjure/tools/delegation_executor.py auto "Analyze large codebase" \
--files src/**/* --requirement large_context
Qwen-Specific Details
For Qwen-specific models, CLI options, cost reference,
and troubleshooting, see modules/qwen-specifics.md.
Exit Criteria
- [ ]
qwen --versionandqwen auth status(orQWEN_API_KEYenv var set) both exit 0
before any task is delegated; missing installation or failed authentication is reported
and stops execution.
- [ ] The delegated task output is saved to
delegations/qwen/YYYYMMDD_HHMMSS.md(timestamp
format matching the Quick Start example), and that file exists on disk after delegation.
- [ ] If
conjure:delegation-coreselected a different provider (Gemini or local), this skill
is not invoked; Qwen delegation only runs when delegation-core explicitly routes to Qwen.
- [ ] Smart delegation via
delegation_executor.py autologs which provider was selected and
why before executing the task, so the selection is auditable.
Other skills for the same job
different authors, same section of the catalogue
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
How to use it
Take athola/qwen-delegation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.