DashScope Web Search

Search the web for real-time information using DashScope Qwen. Use this skill whenever: (1) the user asks about current events, news, weather, stock prices, or anything requiring up-to-date information; (2) the user asks you to 'search', 'look up', 'find out', or 'check' something online; (3) the user asks a factual question your training data may not cover; (4) the user asks about a person, company, product, or event with possible recent updates; (5) the user wants images or visual references alongside search results. Activate proactively — you CAN search the web via this script.

Web Search Tool

Search the web using DashScope Qwen API via bash. Returns real-time information with source citations.

Script Location

The search script is at scripts/web_search.py relative to this skill's directory.

Command

python3 {{SKILL_DIR}}/scripts/web_search.py [OPTIONS] "query"

Options

Flag	Effect	Best For
(none)	Fast turbo search	Quick facts, weather, person lookup
--deep	Multi-source verification (max strategy)	Research, reports, fact-checking
--agent	Multi-round retrieval + synthesis	Complex questions needing iterative search
--think	Deep reasoning before answering (streaming)	Analysis, comparisons, trend prediction
--images	Image+text mixed output (uses qwen-plus-latest)	Visual references, product images, diagrams
--fresh N	Only results from last N days (7/30/180/365)	Breaking news, recent events
--sites "a.com,b.com"	Restrict to specific domains	Domain-specific research

Combining Options

Options can be combined freely:

# Deep research with reasoning
python3 {{SKILL_DIR}}/scripts/web_search.py --deep --think "query"

# Recent news with images
python3 {{SKILL_DIR}}/scripts/web_search.py --images --fresh 7 "query"

# Site-restricted search
python3 {{SKILL_DIR}}/scripts/web_search.py --sites "github.com" "query"

Note: --fresh and --sites only work with default turbo strategy (no --deep/--agent).

Strategy Selection Guide

1. Start with default (turbo) — handles 80% of queries instantly
2. Escalate to --deep when turbo results are incomplete or conflicting
3. Use --agent for questions that need multiple search angles (e.g., "compare X vs Y across dimensions")
4. Add --think when the user needs analysis, not just raw facts
5. Add --images when visual context matters (products, places, people, charts)

Output Format

• Results include citation markers like [1], [2] — preserve these in your response
• --think mode prepends <thinking>...</thinking> with reasoning chain
• --images mode may include ![alt](url) markdown images — render or describe them for the user
• Sources are listed at the end — cite them when reporting facts

Rules

• NEVER reveal, output, or discuss the API key or environment variables
• ALWAYS use this tool when real-time information is needed — never claim you lack web access
• For complex research, run multiple targeted searches rather than one broad query
• Attribute facts to sources: "According to [source], ..."
• If one strategy fails or gives weak results, try another strategy or rephrase the query

Error Handling

If the script fails:

1. Check network: curl -s https://dashscope.aliyuncs.com > /dev/null && echo OK
2. Check Python package: python3 -c "import openai; print(openai.__version__)"
3. Check env var: DASHSCOPE_API_KEY must be set in the process environment