Skill: doahc/tavily-web (version 0.0.3)

--- name: tavily description: Web search and content extraction using Tavily Search/Extract/Research APIs (Bearer auth). Use when you need web results (general/news/finance), date/topic/domain filtering, source citations, or want Tavily instead of built-in web_search/Firecrawl. Requires TAVILY_API_KEY. version: 1.0.0 compatibility: Requires env var TAVILY_API_KEY requires_env: [TAVILY_API_KEY] primary_credential: TAVILY_API_KEY outbound_hosts: ["api.tavily.com"] metadata: hermes: tags: [Web, Search, Tavily, Research, API, Citations] requires_env: [TAVILY_API_KEY] outbound_hosts: ["api.tavily.com"] openclaw: requires: env: ["TAVILY_API_KEY"] --- # Tavily (Web Search / Extract / Research) ## Prereqs - Ensure `TAVILY_API_KEY` is set in the Hermes environment (commonly `~/.hermes/.env`). - Do not hardcode or paste API keys into chat logs. See `references/bp-api-key-management.md`. ## Security Notes - The bundled CLI (`scripts/tavily.py`) reads only `TAVILY_API_KEY` from the environment and only sends requests to `https://api.tavily.com`. - Prefer `search` then `extract` over `include_raw_content` on `search` to keep outputs small and reduce accidental data exposure. ## Quick Reference Use the terminal tool to run the bundled CLI script (prints JSON). `SKILL_DIR` is the directory containing this `SKILL.md` file. ```bash # Search (general) python3 SKILL_DIR/scripts/tavily.py search --query "latest OpenAI API changes" --max-results 5 # Search (news) with recency filter python3 SKILL_DIR/scripts/tavily.py search --query "latest OpenAI API changes" --topic news --time-range week --max-results 5 # High-precision search (more cost/latency) python3 SKILL_DIR/scripts/tavily.py search --query "OpenAI API rate limits March 2026" --search-depth advanced --chunks-per-source 3 --max-results 5 # Search + answer (still cite URLs from results) python3 SKILL_DIR/scripts/tavily.py search --query "What is X?" --include-answer basic --max-results 5 # Extract (targeted chunks; prefer this over include_raw_content on search) python3 SKILL_DIR/scripts/tavily.py extract --url "https://example.com" --query "pricing" --chunks-per-source 3 --format markdown # Research (creates task + polls until complete) python3 SKILL_DIR/scripts/tavily.py research --input "Summarize the EU AI Act enforcement timeline. Provide numbered citations." --model auto --citation-format numbered --max-wait-seconds 180 ``` Use returned `results[].url` fields as citations/sources in your final answer. ## No-Script Option (curl) Use Tavily directly via curl (same endpoints, no bundled script): ```bash curl -s "https://api.tavily.com/search" \ -H "Authorization: Bearer <TAVILY_API_KEY>" \ -H "Content-Type: application/json" \ -d '{"query":"latest OpenAI API changes","topic":"news","time_range":"week","max_results":5}' curl -s "https://api.tavily.com/extract" \ -H "Authorization: Bearer <TAVILY_API_KEY>" \ -H "Content-Type: application/json" \ -d '{"urls":"https://example.com","query":"pricing","chunks_per_source":3,"extract_depth":"basic","format":"markdown"}' ``` ## Procedure 1. Turn the user request into a focused search query (keep it short, ideally under ~400 chars). Split multi-part questions into 2-4 sub-queries. 2. Choose `topic`: - `general` for most searches - `news` for current events (prefer also setting `time_range` or date range) - `finance` for market/finance content 3. Choose `search_depth`: - Start with `basic` (1 credit) unless you need higher precision. - Use `advanced` (2 credits) for high-precision queries; use `chunks_per_source` to control snippet volume. 4. Keep `max_results` small (default 5) and filter by `score` + domain trust. 5. For primary text, run `extract` on 1-3 top URLs: - Provide an `extract --query ... --chunks-per-source N` to avoid dumping full pages into context. 6. For synthesis across multiple subtopics with citations, run `research` and poll until `status=completed`. ## Pitfalls - `include_raw_content` on `search` can explode output size; prefer the two-step flow: `search` then `extract`. - `auto_parameters` can silently pick `search_depth=advanced` (2 credits). Set `--search-depth` explicitly when you care about cost. - `exact_match` is restrictive; wrap the phrase in quotes inside `--query` and expect fewer results. - `country` boosting is only available for `topic=general`. - On failures, keep the `request_id` from responses for support/debugging. ## Verification - Check credits/limits: `python3 SKILL_DIR/scripts/tavily.py usage` - Add `--include-usage` on `search`/`extract` if you want per-request usage info. ## References - `references/search.md` - `references/extract.md` - `references/research.md` - `references/research-get.md` - `references/bp-search.md` - `references/bp-extract.md` - `references/bp-research.md` - `references/bp-api-key-management.md` - `references/usage.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)