Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Perform web searches and generate summarized answers with citations using the Kagi API and FastGPT for higher-quality results or rate-limit fallback.
Perform web searches and generate summarized answers with citations using the Kagi API and FastGPT for higher-quality results or rate-limit fallback.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Use the bundled Python scripts to call Kagiโs API from the OpenClaw host.
Create a token in https://kagi.com/settings/api Export it for your shell/session: export KAGI_API_TOKEN='โฆ' Run a search: python3 scripts/kagi_search.py "haaps glass" --limit 10 --json Or ask FastGPT (LLM + web search): python3 scripts/kagi_fastgpt.py "Summarize the latest Haaps glass mentions" --json
Use when you need a normal ranked list of results (URLs/titles/snippets). Command: python3 scripts/kagi_search.py "<query>" [--limit N] [--json] Notes: Defaults to printing a readable digest; use --json for raw API output. The script automatically sets Authorization: Bot <token>.
Use when you want a short answer grounded in web results, including reference URLs. Command: python3 scripts/kagi_fastgpt.py "<question>" [--cache true|false] [--json]
If Brave Search is rate-limited (429) or you want better results: Use scripts/kagi_search.py to fetch results Then use the main agent model to synthesize / summarize based on the returned URLs/snippets
API reference snippets: references/kagi-api.md Python client + CLIs: scripts/kagi_client.py, scripts/kagi_search.py, scripts/kagi_fastgpt.py
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