web-search

name	web-search
description	Use this skill to search the internet for real-time or up-to-date information. Trigger when the user asks about current events, recent news, live data (weather, prices, scores), unfamiliar topics requiring web verification, or anything that may have changed since the model's knowledge cutoff. Do NOT use for questions answerable from internal corporate knowledge — use rag-query instead.
version	2.0.0

Skill: Web Search (Tavily)

Search the public internet via Tavily API and return structured results for synthesis.

Applicable scenarios:

• Current events, breaking news, recent announcements
• Real-time data: weather, stock prices, sports scores, exchange rates
• Product research, technical documentation, third-party references
• Any fact that may be outdated in the model's training data

---

Execution

Command format (strictly follow — do not modify):

python <DEEPAGENTFORCE_ROOT>/src/services/skills/research/web-search/scripts/web_search.py "<搜索词>" [--max-results N] [--output file.json]

How to determine <DEEPAGENTFORCE_ROOT>:

<DEEPAGENTFORCE_ROOT> is the absolute path to the DeepAgentForce project root on the current host. Resolve it at runtime before executing:

find / -type d -name "DeepAgentForce" 2>/dev/null | head -1
# Example result: /home/user/projects/DeepAgentForce

Parameters:

Parameter	Required	Default	Description
query	✅	—	Search query, wrapped in double quotes
--max-results	❌	5	Number of results to return (suggested: 5–10)
--output	❌	—	Save full JSON response to a file

Examples:

✅ Basic search:

python /home/user/projects/DeepAgentForce/src/services/skills/research/web-search/scripts/web_search.py "2024年诺贝尔奖得主"

✅ More results:

python /home/user/projects/DeepAgentForce/src/services/skills/research/web-search/scripts/web_search.py "latest React 19 features" --max-results 10

✅ Save to file:

python /home/user/projects/DeepAgentForce/src/services/skills/research/web-search/scripts/web_search.py "machine learning trends 2025" --output results.json

❌ Relative path (src/services/...) → execution will fail
❌ Missing quotes around query with spaces → argument parsing error
❌ Using this skill for internal HR/policy questions → use rag-query instead

---

Output Format

The script outputs structured JSON to stdout:

{
  "query": "搜索词",
  "total_results": 5,
  "results": [
    {
      "title": "页面标题",
      "url": "https://...",
      "snippet": "摘要内容（最多500字符）"
    }
  ]
}

Parse this output to synthesize a final answer for the user. Do not return raw JSON directly.