world_bank_open_datalisted

# World Bank Open Data Use this skill to answer questions that require World Bank Open Data country indicators, development metrics, or national-level time series. ## Setup Check whether the agent-gw Python SDK is available in the current Python environment, and install it only if the check fails: ```bash python3 -c "import agent_gw" || python3 -m pip install "$(curl -s https://cdn.kimi.com/agentgw/pysdk/manifest.json | python3 -c "import json,sys; print(json.load(sys.stdin)['latest']['url'])")" ``` The SDK needs an API key from `api_key=...`, `KIMI_API_KEY`, or `~/.kimi/agent-gw.json`. ## Workflow 1. Run `python3 scripts/world_bank_open_data_tool.py describe` from the plugin directory to call `get_data_source_desc({"name": "world_bank_open_data"})`. 2. Read the returned Markdown carefully. It contains the overall data source rules, country formats, indicator formats, date range constraints, and each API's description, required parameters, optional parameters, defaults, and allowed values. 3. Select the API that best matches the user's question. 4. Build `params` exactly from the Markdown requirements. Pay attention to country or region, indicator code or name, year range, unit, source, frequency, and national-level data constraints. 5. Use `python3 scripts/world_bank_open_data_tool.py call` to call `call_data_source_tool`. 6. If the call fails, explain the failure reason from the response. 7. If the call succeeds, save any returned files first, th