Search the live web and 36+ specialised data sources including SEC filings, PubMed, ChEMBL, clinical trials, FRED economic indicators, and patent databases. Use when current, authoritative, or paywalled data is required.
Scanned 9/11/2026
Install to Claude Code
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---
type: Skill
name: valyu
description: Search the live web and 36+ specialised data sources including SEC filings, PubMed, ChEMBL, clinical trials, FRED economic indicators, and patent databases. Use when current, authoritative, or paywalled data is required.
license: MIT
compatibility: Claude Code, Cursor, Gemini CLI, Codex CLI
---
# Valyu — Real-Time Web Search & Specialised Data Access
Use this skill when you need current, authoritative information that is not in your training data or is behind paywalls. Valyu connects to 36+ specialised sources in addition to quality web search.
## When to Use This Skill
- Financial analysis requiring SEC 10-K/10-Q filings
- Biomedical research needing PubMed, ChEMBL, or clinical trial data
- Economic analysis needing FRED or BLS indicators
- Patent research and prior art searches
- Any query requiring information published after your knowledge cutoff
- Fact-checking against authoritative primary sources
## Install
```bash
npx skills add https://github.com/valyuai/skills --skill valyu-best-practices
pip install valyu
```
Set your API key:
```bash
export VALYU_API_KEY=your-api-key
```
## Core API
### Web + specialised search
```python
from valyu import Valyu
client = Valyu(api_key="your-key")
result = client.search(
query="your search query",
search_type="all", # "all" = web + proprietary, "web" = web only, "proprietary" = sources only
max_num_results=10,
relevance_threshold=0.5, # 0-1, higher = stricter
)
for r in result.results:
print(r.title, r.url, r.content)
```
### Targeted source search
```python
# SEC filings
result = client.search(
query="risk factors in latest 10-K for semiconductor companies",
search_type="proprietary",
included_sources=["valyu/valyu-sec-filings"],
max_num_results=5,
)
# Biomedical cross-search
result = client.search(
query="GLP-1 receptor agonists drug interactions clinical outcomes",
search_type="all",
included_sources=[
"valyu/valyu-pubmed",
"valyu/valyu-chembl",
"valyu/valyu-clinical-trials",
],
max_num_results=10,
)
# Economic data
result = client.search(
query="US inflation rate Q1 2026 CPI components",
search_type="proprietary",
included_sources=["valyu/valyu-fred"],
max_num_results=5,
)
```
### Direct cited answer (Answer API)
Use when you need a grounded, cited response rather than raw documents:
```python
answer = client.context(
query="What were the key risk factors disclosed by NVIDIA in their most recent 10-K?",
search_type="proprietary",
max_num_results=5,
)
print(answer.context) # Synthesised answer with citations
```
## Available Specialised Sources
| Category | Sources |
|----------|---------|
| Financial | SEC filings (10-K, 10-Q, 8-K), earnings transcripts |
| Biomedical | PubMed, ChEMBL (2.5M compounds), ClinicalTrials.gov |
| Economic | FRED, BLS, World Bank indicators |
| Legal/Patent | USPTO, EPO patent databases |
| Academic | CrossRef, arXiv, Semantic Scholar |
| Web | Quality-filtered live web search |
## Best Practices
1. **Be specific about sources** — use `included_sources` to target the data type you need
2. **Always surface citations** — return source URLs to users so they can verify
3. **Use `search_type="all"`** for broad research; `"proprietary"` for authoritative data
4. **Set `relevance_threshold`** higher (0.7+) when you need precise matches
5. **Handle empty results** gracefully — fall back to broader query if needed
## Error Handling
```python
try:
result = client.search(query=query, search_type="all", max_num_results=5)
if not result.results:
# Widen the query or try a different source
...
except Exception as e:
# Log and inform the user; do not hallucinate a substitute answer
...
```
## Performance Benchmarks
| Benchmark | Valyu | Google | Exa |
|-----------|-------|--------|-----|
| FreshQA (600 time-sensitive queries) | **79%** | 39% | 24% |
| Finance-specific queries | **73%** | 55% | — |
| MedAgent (562 medical queries) | **48%** | — | — |
## Tips
- Never fabricate data when Valyu returns no results — tell the user and suggest alternative queries
- For streaming large result sets, use pagination parameters
- Cite sources inline in your response: "According to [Source Title](URL)…"
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