Search the web and ingest results as wiki pages
npx skills add https://github.com/axoviq-ai/synthadoc --skill web_search
Accepts a natural language query, calls the Tavily AI search API, and
returns the top matching URLs. Your agent receives those URLs and decides
what to do with them — fetch each one, display them, pass them to another
skill, etc.
1. Install the dependency:
pip install tavily-python
2. Set your Tavily API key (free tier: 1,000 searches/month — sign up at
https://tavily.com, no credit card required):
# macOS / Linux
export TAVILY_API_KEY="tvly-your-key-here"
# Windows (Command Prompt)
set TAVILY_API_KEY=tvly-your-key-here
# Windows (PowerShell)
$env:TAVILY_API_KEY = "tvly-your-key-here"
3. Optional — cap the number of results (default: 20):
export SYNTHADOC_WEB_SEARCH_MAX_RESULTS=10
import asyncio
from synthadoc.skills.web_search.scripts.main import WebSearchSkill
skill = WebSearchSkill()
async def main():
result = await skill.extract("search for: transformer architecture papers")
urls = result.metadata["child_sources"] # list[str] — top matching URLs
query = result.metadata["query"] # "transformer architecture papers"
print(f"Found {len(urls)} URLs for '{query}':")
for url in urls:
print(" ", url)
asyncio.run(main())
result.text is always empty — the skill is a discovery step that returns
URLs, not page content. Pass the URLs to the url or youtube skill (or
your own HTTP client) to fetch content.
The skill strips a leading intent phrase before sending the query to Tavily:
| Input | Query sent to Tavily |
|---|---|
| search for: RAG evaluation | RAG evaluation |
| find on the web: LLM benchmarks | LLM benchmarks |
| look up quantum computing | quantum computing |
| youtube: Karpathy transformers | Karpathy transformers (YouTube only) |
| 搜索: 深度学习架构 | 深度学习架构 |
YouTube-specific prefixes (youtube:, search youtube:, youtube video:,
etc.) restrict the Tavily search to youtube.com and youtu.be.
CJK intent phrases supported: 查找, 搜索, 网络搜索, 在网上查, 查一下
A built-in blocklist skips sites that block automated HTTP clients:
reddit.com, medium.com, quora.com, twitter.com/x.com,
linkedin.com, wikipedia.org, IEEE Xplore, ACM DL, and common
subscription-only academic publishers.
If SYNTHADOC_WIKI_ROOT is set, the skill also loads
$SYNTHADOC_WIKI_ROOT/.synthadoc/blocked_domains.json (a JSON array of
domain strings) to extend the blocklist at runtime.
scripts/main.py — WebSearchSkill: intent parsing, domain filtering,returns child_sources in metadata
scripts/fetcher.py — thin async wrapper around AsyncTavilyClientassets/search-providers.json — search provider registry (currently Tavily)When running inside Synthadoc, the Orchestrator reads child_sources from
the result metadata and automatically enqueues each URL as a separate ingest
job, which are then processed by the url or youtube skill. No additional
setup is required beyond the env vars above.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take axoviq-ai/web_search from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.