skills/baidu-search/SKILL.md
Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.
npx skillsauth add baidubce/skills baidu-searchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Search the web via Baidu AI Search API.
This skill requires a BAIDU_API_KEY to be configured in OpenClaw.
If you don't have an API key yet, please visit: https://console.bce.baidu.com/ai-search/qianfan/ais/console/apiKey
For detailed setup instructions, see: references/apikey-fetch.md
python3 skills/baidu-search/scripts/search.py '<JSON>'
| Param | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | query | str | yes | - | Search query | | count | int | no | 10 | Number of results to return, range 1-50 | | freshness | str | no | Null | Time range, two formats: format one is ”YYYY-MM-DDtoYYYY-MM-DD“, and format two includes pd, pw, pm, and py, representing the past 24 hours, past 7 days, past 31 days, and past 365 days respectively |
# Basic search
python3 scripts/search.py '{"query":"人工智能"}'
# Freshness first format "YYYY-MM-DDtoYYYY-MM-DD" example
python3 scripts/search.py '{
"query":"最新新闻",
"freshness":"2025-09-01to2025-09-08"
}'
# Freshness second format pd、pw、pm、py example
python3 scripts/search.py '{
"query":"最新新闻",
"freshness":"pd"
}'
# set count, the number of results to return
python3 scripts/search.py '{
"query":"旅游景点",
"count": 20,
}'
Fully functional.
development
Generate interactive visualization pages for feasible solutions produced by Famou evolutionary algorithms. Use this skill when the user mentions "Famou visualization", "visualize this solution", "show feasible solution results", "evolution results", "evolve visualization", or provides a Python-code solution (path planning, scheduling, knapsack, TSP, job scheduling, machine learning, etc.) that needs to be displayed visually. Even if the user just says "help me visualize this solution", "draw it out", or "show me the results", trigger this skill immediately whenever the context involves evolutionary algorithms or optimization problem solutions.
testing
Workflow skill for managing famou evolutionary experiment tasks, including public normal mode and public pro hybrid mode. Use this skill when the user mentions "submit experiment", "check experiment status", "delete experiment", "get experiment results", "account info", "quota", "credits", "famou experiment", "upload experiment", "config.yaml experiment", "hybrid mode", or needs to use famou-ctl to manage experiment tasks. Even if the user just says "submit" or "run experiment", trigger this skill whenever the context involves the famou platform.
development
A data analysis skill for understanding datasets, analyzing data, building data processing pipelines, and summarizing analytical results. Use this skill when the user mentions "analyze data", "data processing", "data exploration", "statistical analysis", "data cleaning", "data summarization", "create a data report", "understand this dataset", or "take a look at this CSV/Excel/dataset". Even if the user simply says "help me look at this data" or "analyze this", trigger this skill whenever the context involves a data file or dataset. Also invoke this skill if data analysis is required during Famou problem definition.
testing
Interactive end-to-end Famou workflow for defining, implementing, and solving optimization tasks. The workflow typically proceeds in three stages: (1) understand the data and define the task, producing `problem.md`; (2) implement and validate `evaluator.py`, `init.py`, and `prompt.md` from the task definition; (3) run deep solving through Famou. Trigger this skill whenever the user wants to define, clarify, create, or fix a Famou task; prepare Famou experiment artifacts; write or update `problem.md`, `evaluator.py`, `init.py`, or `prompt.md`; run Famou; do deep solving; or solve an optimization, ML, or search problem with evolutionary methods. Even if the user simply says "help me make a Famou task", "help me solve this", or "run Famou", trigger this skill whenever the surrounding context indicates an optimization or search task. Also trigger when the user describes a combinatorial optimization, scheduling, routing, or ML problem without mentioning Famou — treat it as a potential Famou task.