[Skill] Add open-source-engineer-schedule-planning-master skill

[shen-shanshan]

描述

This skill is designed to assist open source engineers in planning their schedules effectively. It provides tools and resources for managing feature development, PR review, Issue resolution, information acquisition, and more. By using this skill, engineers can optimize their time and ensure that they are focusing on the most important tasks.

相关 Issue

No.

变更类型

• Bug 修复
• 新功能
• 代码重构
• 文档更新
• 样式改进
• 性能优化
• 测试相关
• 其他

输出示例

📅 Weekly Schedule for Open Source Engineer

Week of February 12 - February 18, 2026
Engineer: shen-shanshan
Focus Repositories: vllm-project/vllm, vllm-project/vllm-ascend
Focus Areas: Multi-modal, Structured Output, Elastic Scaling

---

📋 Task Overview

Priority 1: 🚀 Optimize Qwen3-VL Performance

• Deadline: April 1, 2026
• Duration: ~2 weeks (Week 1 of 2)
• Status: In Progress
• Description: Performance optimization work for Qwen3-VL model to improve inference speed and efficiency

Priority 2: 🐛 Resolve Multi-modal Issues in vllm-ascend

• Focus: VL, Omni, OCR models and issues assigned to you
• Key Issue Identified: 1 critical issue assigned to you (#6533)
• Description: Address bugs and issues related to multi-modal models in the vllm-ascend repository

Priority 3: 🔍 Review Multi-modal PRs in vllm-ascend

• Focus: Multi-modal related pull requests
• Description: Review and provide feedback on community contributions related to multi-modal models

Priority 4: 📰 Keep Up with LLM News

• Focus: Recent developments in multi-modal models and vLLM ecosystem
• Description: Stay informed about latest research, model releases, and industry trends

---

📆 Daily Schedule

Monday, February 12, 2026

1. Priority 1: 🚀 Qwen3-VL Performance Optimization

   • Begin Week 1 of performance optimization work
   • Set up profiling environment and baseline benchmarks
   • Identify performance bottlenecks in inference pipeline

2. Priority 2: 🐛 Critical Bug - Qwen3-VL Inference Output Anomaly

   • Issue #6533 - ASSIGNED TO YOU ⚠️
   • Title: "[Bug]: vllm-ascend:v0.14.0rc1 910B4, Qen3-VL-8B-Instruct 推理输出异常"
   • Author: zhongqing0507
   • Labels: bug, module:multimodal
   • Summary: Qwen3-VL-8B-Instruct produces abnormal inference output with repetitive text on vllm-ascend v0.14.0rc1 with 910B4 hardware. The model outputs repetitive fragments like "你好，，，我是一个AI，我叫Qwen，我是Qwen，，我叫，我，我是..." instead of coherent responses.
   • Action: Investigate root cause, reproduce the issue, and develop a fix

3. Priority 3: 🔍 Review Upstream Multi-modal PRs

   • PR #34398 - Add COLQwen3 code & Inference
   • Author: craftsangjae (Kata Coder)
   • Labels: documentation, new-model, multi-modality, qwen
   • Summary: Adds native support for ColQwen3 multi-modal late interaction models in vLLM. ColQwen3 extends Qwen3-VL with a linear projection head for per-token L2-normalized embeddings, enabling MaxSim late interaction scoring for document retrieval and reranking across text and image inputs. Supports TomoroAI and OpenSearch-AI model families.
   • Action: Review implementation, test examples, and provide feedback

Tuesday, February 13, 2026

1. Priority 1: 🚀 Qwen3-VL Performance Optimization

   • Analyze profiling results from Monday
   • Implement initial optimization strategies (memory management, kernel optimization)
   • Run preliminary benchmark tests

2. Priority 2: 🐛 Continue Work on Issue #6533

   • Test potential fixes for the inference output anomaly
   • Validate fix across different hardware configurations
   • Prepare patch for review

3. Priority 3: 🔍 Review Multi-modal Bugfix PR

   • PR #34358 - Standardize getting number of image patches/tokens
   • Author: DarkLight1337 (Cyrus Leung)
   • Labels: bug, ready, multi-modality
   • Summary: Bugfix that considers mm_kwargs when determining number of image tokens, disallows passing processor=None to simplify code, and fixes Idefics3 and SmolVLM tests not passing mm_kwargs to reference processor call.
   • Action: Review changes and verify test coverage

Wednesday, February 14, 2026

1. Priority 1: 🚀 Qwen3-VL Performance Optimization

   • Evaluate benchmark results from Tuesday
   • Fine-tune optimization parameters
   • Document performance improvements and findings

2. Priority 2: 🐛 Submit Fix for Issue #6533

   • Create PR with fix for Qwen3-VL inference output anomaly
   • Write comprehensive test cases
   • Update documentation if needed

3. Priority 4: 📰 LLM News and Research

   • Review recent papers on multi-modal model optimization
   • Check for new model releases (DeepSeek-OCR-2, Phi-4-multimodal updates)
   • Monitor vLLM community discussions and feature requests

Thursday, February 15, 2026

1. Priority 1: 🚀 Qwen3-VL Performance Optimization

   • Implement advanced optimization techniques based on Wednesday's analysis
   • Test optimization across different model sizes (8B, 32B variants)
   • Prepare mid-week progress report

2. Priority 3: 🔍 Review Whisper Multi-modal Enhancement

   • PR #34366 - Add language detection feature to Whisper
   • Author: warichet
   • Labels: performance, multi-modality, and others
   • Summary: Introduces automatic language detection for Whisper model. When language field is not specified, the model automatically detects the language of audio input using the <|startoftranscript|> token in decoder prompt. Defaults to English if detection fails.
   • Action: Review implementation and test with various audio inputs

3. Priority 3: 🔍 Review Additional Multi-modal PR

   • PR #34342 - Add automatic language detection for Whisper transcription
   • Author: spacecheck (Roman)
   • Labels: frontend, multi-modality
   • Summary: Frontend implementation for automatic language detection in Whisper transcription
   • Action: Review frontend integration and API changes

Friday, February 16, 2026

1. Priority 1: 🚀 Qwen3-VL Performance Optimization

   • Finalize Week 1 optimization work
   • Run comprehensive benchmark suite
   • Prepare detailed progress report with performance metrics
   • Plan Week 2 optimization targets

2. Priority 2: 🐛 Address PR Feedback for Issue #6533

   • Respond to review comments on your PR
   • Make necessary adjustments
   • Coordinate with maintainers for merge timeline

3. Priority 3: 🔍 Review Whisper Test Fix

   • PR #34324 - Fixed whisper CPU test that does not spawn properly
   • Author: almayne
   • Labels: multi-modality
   • Summary: Fixes Whisper CPU test spawning issues
   • Action: Quick review and approval if tests pass

4. Priority 4: 📰 Weekly LLM News Summary

   • Compile weekly summary of important LLM developments
   • Focus on multi-modal model advancements and vLLM ecosystem updates
   • Share insights with team

Weekend Planning (February 17-18, 2026)

• Review week's accomplishments and lessons learned
• Plan detailed tasks for Week 2 of Qwen3-VL optimization
• Prepare for upcoming multi-modal model support requests
• Optional: Explore new multi-modal architectures and techniques

---

🎯 Key Focus Areas This Week

1. 🚀 Qwen3-VL Performance Optimization (Priority 1)

This is your primary focus for the week. Allocate approximately 50-60% of your time to this task. Key activities include:

• Performance profiling and bottleneck identification
• Implementation of optimization strategies (memory management, kernel optimization, batching improvements)
• Benchmark testing and validation across different model sizes
• Documentation of findings and performance improvements
• Preparation for Week 2 optimization work

Expected Outcome: Measurable performance improvements with detailed metrics and clear plan for Week 2.

2. 🐛 Critical Bug Resolution (Priority 2)

Focus on the issue assigned to you (#6533) - Qwen3-VL inference output anomaly:

• Issue #6533: Qwen3-VL-8B-Instruct produces repetitive, incoherent output on vllm-ascend v0.14.0rc1 with 910B4 hardware
• This is a critical bug affecting production deployments
• Requires investigation, fix development, testing, and PR submission

Expected Outcome: Root cause identified, fix implemented and submitted as PR with comprehensive tests.

3. 🔍 Multi-modal PR Reviews (Priority 3)

Review and provide feedback on community contributions related to multi-modal models:

• ColQwen3 Support (PR #34398): New model integration for late interaction retrieval
• Image Token Standardization (PR #34358): Bugfix for multi-modal processing
• Whisper Language Detection (PR #34366, #34342): Audio model enhancement
• Whisper Test Fix (PR #34324): CI/test improvement
• Voxtral Test Refactoring (PR #34294): Test infrastructure improvement

Expected Outcome: Provide constructive feedback on at least 3-4 PRs, helping maintainers make merge decisions.

4. 📰 LLM Ecosystem Awareness (Priority 4)

Stay informed about latest developments in multi-modal models and vLLM ecosystem:

• Monitor new model releases (DeepSeek-OCR-2, Phi-4-multimodal, Step3-VL, etc.)
• Review recent research papers on multi-modal optimization
• Track vLLM community discussions and feature requests
• Identify potential collaboration opportunities

Expected Outcome: Weekly summary of key developments and insights to share with team.

---

📝 Important Notes

Recent Developments to Monitor

1. 🔥 vLLM Upstream Activity:

   • Significant activity around Qwen3-VL improvements and new model integrations
   • ColQwen3 support being added for late interaction retrieval use cases
   • Whisper model enhancements with automatic language detection
   • Multi-modal processing standardization efforts (image token handling)
   • Active development on audio models (Whisper, Voxtral)

2. ⚠️ vllm-ascend Specific Issues:

   • Critical: Issue #6533 assigned to you requires immediate attention
   • Multiple Qwen3-VL related bugs reported in the past week
   • Hardware-specific issues on 910B4 platform need investigation
   • Performance optimization opportunities identified

3. 🆕 New Multi-modal Models:

   • ColQwen3: Late interaction retrieval model extending Qwen3-VL
   • DeepSeek-OCR-2: OCR capabilities (support requested)
   • Phi-4-multimodal: Vision-Language model (support requested)
   • Step3-VL-10B: Vision-Language model (support requested)

Collaboration Opportunities

• Upstream vLLM Maintainers: Share findings from Qwen3-VL optimization work, especially performance improvements that could benefit upstream
• DarkLight1337 (Cyrus Leung): Collaborate on multi-modal processing standardization (PR #34358)
• craftsangjae: Provide feedback on ColQwen3 implementation (PR #34398)
• Community Contributors: Help review and test Whisper enhancements and other multi-modal PRs
• vllm-ascend Team: Coordinate on hardware-specific optimizations and bug fixes

Blockers and Risks

• ⚠️ Issue #6533 is critical and assigned to you - requires immediate attention to unblock users
• ⚠️ Multiple Qwen3-VL bugs may indicate systemic issues requiring deeper investigation beyond individual fixes
• ⚠️ Hardware-specific issues (910B4) may require access to specific hardware for debugging
• ⚠️ Performance optimization deadline (April 1) requires steady progress - Week 1 is crucial for establishing baseline and approach
• ⚠️ New model support requests may require significant testing and validation effort - prioritize based on community demand

Success Metrics for This Week

✅ Complete Week 1 of Qwen3-VL optimization with measurable performance improvements (target: 10-20% improvement in inference speed)
✅ Resolve or make significant progress on issue #6533 with PR submitted for review
✅ Review and provide feedback on at least 3-4 multi-modal PRs to support community contributions
✅ Triage and prioritize new multi-modal model support requests based on community needs
✅ Compile weekly LLM news summary to share with team

---

Note: This schedule is flexible and should be adjusted based on urgent issues, stakeholder priorities, and progress on the Qwen3-VL optimization work. Stay agile and communicate proactively with maintainers and stakeholders about any blockers or changes in priorities. 🚀

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