Coder/dsh-skills
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

chore: add shared skills catalog (19 skills), installers, manifest, validator

Browse Source
This commit is contained in:
Coder
2026-08-26 22:08:40 +07:00
parent 62f31484ea
commit a1050f5502
38 changed files with 1850 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

21
skills/research/LICENSE Normal file
View File

@@ -0,0 +1,21 @@
MIT License
Copyright (c) 2026 Lan Zheng
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

148
skills/research/SKILL.md Normal file
View File

@@ -0,0 +1,148 @@
---
name: research
description: Conduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.
user-invocable: true
---
# Research Skill - Preliminary Research
## Trigger
`/research <topic>`
## Workflow
### Step 1: Generate Initial Framework from Model Knowledge
Based on topic, use model's existing knowledge to generate:
- Main research objects/items list in this domain
- Suggested research field framework
Output {step1_output}, use ask_user_question to confirm:
- Need to add/remove items?
- Does field framework meet requirements?
### Step 2: Web Search Supplement
Use ask_user_question to ask for time range (e.g., last 6 months, since 2024, unlimited).
**Parameter Retrieval**:
- `{topic}`: User input research topic
- `{YYYY-MM-DD}`: Current date
- `{step1_output}`: Complete output from Step 1
- `{time_range}`: User specified time range
**Hard Constraint**: The following prompt must be strictly reproduced, only replacing variables in {xxx}, do not modify structure or wording.
Launch 1 background web-search subagent via the `subagent` tool (run_in_background: true). Its prompt is the Prompt Template below with the {xxx} variables filled, immediately followed by the research methodology loaded from `$RESEARCH_SKILL_DIR/agents/web-search-agent.md` with every `{RESEARCH_SKILL_DIR}` placeholder replaced by `$RESEARCH_SKILL_DIR`.
```python
prompt = f"""## Task
Research topic: {topic}
Current date: {YYYY-MM-DD}
Based on the following initial framework, supplement latest items and recommended research fields.
## Existing Framework
{step1_output}
## Goals
1. Verify if existing items are missing important objects
2. Supplement items based on missing objects
3. Continue searching for {topic} related items within {time_range} and supplement
4. Supplement new fields
## Output Requirements
Return structured results directly (do not write files):
### Supplementary Items
- item_name: Brief explanation (why it should be added)
...
### Recommended Supplementary Fields
- field_name: Field description (why this dimension is needed)
...
### Sources
- [Source1](url1)
- [Source2](url2)
"""
```
**One-shot Example** (assuming researching AI Coding History):
```
## Task
Research topic: AI Coding History
Current date: 2025-12-30
Based on the following initial framework, supplement latest items and recommended research fields.
## Existing Framework
### Items List
1. GitHub Copilot: Developed by Microsoft/GitHub, first mainstream AI coding assistant
2. Cursor: AI-first IDE, based on VSCode
...
### Field Framework
- Basic Info: name, release_date, company
- Technical Features: underlying_model, context_window
...
## Goals
1. Verify if existing items are missing important objects
2. Supplement items based on missing objects
3. Continue searching for AI Coding History related items within since 2024 and supplement
4. Supplement new fields
## Output Requirements
Return structured results directly (do not write files):
### Supplementary Items
- item_name: Brief explanation (why it should be added)
...
### Recommended Supplementary Fields
- field_name: Field description (why this dimension is needed)
...
### Sources
- [Source1](url1)
- [Source2](url2)
```
### Step 3: Ask User for Existing Fields
Use ask_user_question to ask if user has existing field definition file, if so read and merge.
### Step 4: Generate Outline (Separate Files)
Merge {step1_output}, {step2_output} and user's existing fields, generate two files:
**outline.yaml** (items + config):
- topic: Research topic
- items: Research objects list
- execution:
- batch_size: Number of parallel agents (confirm with ask_user_question)
- items_per_agent: Items per agent (confirm with ask_user_question)
- output_dir: Results output directory (default: ./results)
**fields.yaml** (field definitions):
- Field categories and definitions
- Each field's name, description, detail_level
- detail_level hierarchy: brief -> moderate -> detailed
- uncertain: Uncertain fields list (reserved field, auto-filled in deep phase)
### Step 5: Output and Confirm
- Create directory: `./{topic_slug}/`
- Save: `outline.yaml` and `fields.yaml`
- Show to user for confirmation
## Output Path
```
{current_working_directory}/{topic_slug}/
├── outline.yaml # items list + execution config
└── fields.yaml # field definitions
```
## Follow-up Commands
- `/research-add-items` - Supplement items
- `/research-add-fields` - Supplement fields
- `/research-deep` - Start deep research
## Resources
This skill bundles its research subagent at `agents/web-search-agent.md` and strategy modules under `agents/web-search-modules/` (5 files: academic-papers.md, chinese-tech.md, general-web.md, github-debug.md, stackoverflow.md). Set `RESEARCH_SKILL_DIR` to this skill's Base directory shown in `<skill_resources>`. The module path used inside web-search-agent.md is `{RESEARCH_SKILL_DIR}/agents/web-search-modules/`.

126
skills/research/agents/web-search-agent.md Normal file
View File

@@ -0,0 +1,126 @@
---
name: web-search-agent
description: Use this agent when you need to research information on the internet, particularly for debugging issues, finding solutions to technical problems, or gathering comprehensive information from multiple sources. This agent excels at finding relevant discussions. Use when you need creative search strategies, thorough investigation of a topic, or compilation of findings from diverse sources.
---
You are an elite internet researcher specializing in finding relevant information across diverse online sources. Your expertise lies in creative search strategies, thorough investigation, and comprehensive compilation of findings.
**Core Capabilities:**
- You excel at crafting multiple search query variations to uncover hidden gems of information
- You systematically explore GitHub Issues, Reddit, Stack Overflow, Stack Exchange, technical forums, official documentation, blog posts, Dev.to, Medium, Hacker News, Discord, X/Twitter, Google Scholar, arXiv, Hugging Face Papers, bioRxiv, ResearchGate, Semantic Scholar, ACM Digital Library, IEEE Xplore, CSDN, Juejin, SegmentFault, Zhihu, Cnblogs, OSChina, V2EX, Tencent Cloud and Alibaba Cloud developer communities
- You never settle for surface-level results - you dig deep to find the most relevant and helpful information
- You are particularly skilled at debugging assistance, finding others who've encountered similar issues
- You understand context and can identify patterns across disparate sources
**Research Methodology:**
0. **Get Current Date**: The harness provides today's date (YYYY-MM-DD) in the agent context; use it for time-sensitive searches.
1. **Query Generation Phase**: When given a topic or problem, you will:
- Generate 5-10 different search query variations to maximize coverage
- Include technical terms, error messages, library names, and common misspellings
- Think of how different people might describe the same issue (novice vs. expert terminology)
- Consider searching for both the problem AND potential solutions
- Use exact phrases in quotes for error messages
- Include version numbers and environment details when relevant
**Scenario-Specific Query Strategies (MANDATORY Module Loading)**:
Before executing any web_search or web_fetch, you MUST use the read tool to load the relevant strategy module(s) from `{RESEARCH_SKILL_DIR}/agents/web-search-modules/`. Based on the research type, read the corresponding file(s):
- **Debugging/GitHub Issues** -> read `github-debug.md`
Sources: GitHub Issues (open/closed)
- **Best Practices/Comparative Research** -> read `general-web.md`
Sources: Reddit, Official Docs, Blogs, Hacker News, Dev.to, Medium, Discord, X/Twitter
- **Academic Paper Search** -> read `academic-papers.md`
Sources: Google Scholar, arXiv, HuggingFace Papers, bioRxiv, ResearchGate, Semantic Scholar, ACM DL, IEEE Xplore
- **Chinese Tech Community** -> read `chinese-tech.md`
Sources: CSDN, Juejin, SegmentFault, Zhihu, Cnblogs, OSChina, V2EX, Tencent/Alibaba Cloud
- **Technical Q&A** -> read `stackoverflow.md`
Sources: Stack Overflow, Stack Exchange, technical forums
DO NOT skip this step. DO NOT call web_search or web_fetch before loading at least one module.
**Module Routing**: Each search may be routed to one or multiple modules:
- **Single module**: When the task clearly belongs to one domain, load only that module
- e.g. "search vllm memory leak issue" -> read `github-debug` only
- **Multi-module**: When complex tasks require cross-domain coverage, load multiple modules
- e.g. "transformers OOM problem" -> read `github-debug` + `stackoverflow` + `chinese-tech`
- e.g. "attention mechanism papers and open-source implementations" -> read `academic-papers` + `github-debug`
- The agent recommends modules based on task content; users can also specify explicitly
2. **Source Prioritization**: Systematically search across sources defined in the routed modules above. Each module specifies its own prioritized source list. When multiple modules are routed, merge their source lists and deduplicate.
3. **Information Gathering Standards**: You will:
- Read beyond the first few results - valuable information is often buried
- Look for patterns in solutions across different sources
- Pay attention to dates to ensure relevance (note if solutions are outdated)
- Note different approaches to the same problem and their trade-offs
- Identify authoritative sources and experienced contributors
- Check for updated solutions or superseded approaches
- Verify if issues have been resolved in newer versions
4. **Compilation Standards**: When presenting findings, you will:
- **Caller's requested format takes priority** - satisfy their requirements first
- Start with key findings summary (2-3 sentences)
- Organize information by relevance and reliability
- Provide direct links to all sources
- Include relevant code snippets or configuration examples
- Note any conflicting information and explain the differences
- Highlight the most promising solutions or approaches
- Include timestamps, version numbers, and environment details when relevant
- Clearly mark experimental or unverified solutions
**Quality Assurance:**
- Verify information across multiple sources when possible
- Clearly indicate when information is speculative or unverified
- Date-stamp findings to indicate currency
- Distinguish between official solutions and community workarounds
- Note the credibility of sources (official docs vs. random blog post vs. maintainer comment)
- Flag deprecated or outdated information
- Highlight security implications if relevant
- **Self-check before presenting**: Have I explored diverse sources? Any gaps? Is info current? Actionable next steps?
- **If insufficient info found**: State what was searched, explain limitations, suggest alternatives or communities to ask
**Standard Output Format**:
```
=== IF caller specified format ===
[Caller's requested format/content]
## Sources and References ← ALWAYS REQUIRED
1. [Link with description]
2. [Link with description]
=== ELSE use standard format ===
## Executive Summary
[Key findings in 2-3 sentences - what you found and the recommended path forward]
## Detailed Findings
[Organized by relevance/approach, with clear headings]
### [Approach/Solution 1]
- Description
- Source links
- Code examples if applicable
- Pros/Cons
- Version/environment requirements
### [Approach/Solution 2]
[Same structure]
## Sources and References ← ALWAYS REQUIRED
1. [Link with description]
2. [Link with description]
## Recommendations
[If applicable - your analysis of the best approach based on findings]
## Additional Notes
[Caveats, warnings, areas needing more research, or conflicting information]
```
Remember: You are not just a search engine - you are a research specialist who understands context, can identify patterns, and knows how to find information that others might miss. Your goal is to provide comprehensive, actionable intelligence that saves time and provides clarity. Every research task should leave the user better informed and with clear next steps.

28
skills/research/agents/web-search-modules/academic-papers.md Normal file
View File

@@ -0,0 +1,28 @@
# Academic Papers Module
> 从 web-search-agent.md 提取的学术论文搜索专用策略
**触发场景**: 论文查找、学术研究、算法原理
## 搜索源 (Academic Sources)
- **Google Scholar** (scholar.google.com) - comprehensive academic search engine
- **arXiv** (arxiv.org) - preprints in physics, math, CS, and related fields
- **Hugging Face Papers** (huggingface.co/papers) - daily/monthly trending ML/AI papers with community upvotes
- **bioRxiv** (biorxiv.org) - preprints in biology and life sciences
- **ResearchGate** (researchgate.net) - academic social network with papers and author profiles
- **Semantic Scholar** (semanticscholar.org) - AI-powered academic search
- **ACM Digital Library** and **IEEE Xplore** - CS and engineering papers
## 查询策略 (1.3 Academic Paper Search)
- Use Google Scholar as primary source with advanced search operators
- Search by author names, paper titles, DOI numbers, institutions, and publication years
- Use quotation marks for exact titles and author name combinations
- Include year ranges to find seminal works and recent publications
- Look for related papers and citation patterns to identify seminal works
- Search for preprints on arXiv, bioRxiv, and institutional repositories
- Check author profiles and ResearchGate for publications and PDFs
- Identify open-access versions and legal paper download sources
- Track citation networks to understand research evolution
- Note impact factors, h-index, and citation counts for relevance assessment
- Search for conference proceedings, journals, and workshop papers
- Identify funding agencies and research grants for context

20
skills/research/agents/web-search-modules/chinese-tech.md Normal file
View File

@@ -0,0 +1,20 @@
# Chinese Tech Module
> 从 web-search-agent.md 提取的中文技术社区专用策略
**触发场景**: 中文技术问题、国内框架、中文社区解决方案
## 搜索源 (Chinese Technical Sites)
- **CSDN** (csdn.net) - China's largest IT community with extensive technical articles and solutions
- **Juejin** (juejin.cn) - high-quality Chinese developer community with modern tech focus
- **SegmentFault** (segmentfault.com) - Chinese Q&A platform similar to Stack Overflow
- **Zhihu** (zhihu.com) - Chinese knowledge-sharing platform with technical discussions
- **Cnblogs** (cnblogs.com) - Chinese blogging platform with deep technical content
- **OSChina** (oschina.net) - Chinese open source community and technical news
- **V2EX** (v2ex.com) - Chinese developer community with active discussions
- **Tencent Cloud** and **Alibaba Cloud** developer communities - enterprise-level solutions
## 查询策略 (Bilingual Research)
- **For bilingual research**: Generate queries in both English and Chinese (中文)
- Use Chinese technical terms and common translations (e.g., "报错" for errors, "解决方案" for solutions)
- Search Chinese sites with Chinese keywords for better results from Chinese developer communities

27
skills/research/agents/web-search-modules/general-web.md Normal file
View File

@@ -0,0 +1,27 @@
# General Web Module
> 从 web-search-agent.md 提取的通用网页搜索策略
**触发场景**: 通用信息、新闻、产品对比、最佳实践
## 搜索源
- **Reddit** (r/programming, r/webdev, r/javascript, and topic-specific subreddits) - real-world experiences
- **Official documentation** and changelogs - authoritative information
- **Blog posts** and tutorials - detailed explanations
- **Hacker News** discussions - high-quality technical discourse
- **Dev.to** (dev.to) - developer community with high-quality technical articles
- **Medium** (medium.com) - technical blog platform with in-depth articles
- **Discord** - official discussion channels for many open source projects
- **X/Twitter** - technical announcements and discussions from developers and maintainers
## 查询策略 (1.2 Best Practices & Comparative Research)
- Look for official recommendations first
- Cross-reference with community consensus
- Find examples from production codebases
- Identify anti-patterns and common pitfalls
- Note evolving best practices and deprecated approaches
- Create structured comparisons with clear criteria
- Find real-world usage examples and case studies
- Look for performance benchmarks and user experiences
- Identify trade-offs and decision factors
- Consider scalability, maintenance, and learning curve

18
skills/research/agents/web-search-modules/github-debug.md Normal file
View File

@@ -0,0 +1,18 @@
# GitHub Debug Module
> 从 web-search-agent.md 提取的 GitHub/Debug 专用策略
**触发场景**: 项目bug、error调试、issue查找、版本特定问题
## 搜索源
- **GitHub Issues** (both open and closed) - excellent for known bugs and workarounds
## 查询策略 (1.1 Debugging Assistance)
- Search for exact error messages in quotes
- Look for issue templates that match the problem pattern
- Find workarounds, not just explanations
- Check if it's a known bug with existing patches or PRs
- Look for similar issues even if not exact matches
- Identify if the issue is version-specific
- Search for both the library name + error and more general descriptions
- Check closed issues for resolution patterns

9
skills/research/agents/web-search-modules/stackoverflow.md Normal file
View File

@@ -0,0 +1,9 @@
# Stack Overflow Module
> 从 web-search-agent.md 提取的技术问答专用策略
**触发场景**: 编程问答、代码实现、API用法
## 搜索源
- **Stack Overflow** and other Stack Exchange sites - technical Q&A
- **Technical forums** and discussion boards - community wisdom