This guide covers the anatomy of workflow templates and best practices for creating effective, reusable research workflows.
Template Anatomy
A workflow template consists of:
| Field | Required | Description |
|---|
name | Yes | Template name for identification |
prompt | Yes | Research prompt with Jinja2 placeholders |
description | No | Human-readable description |
expected_input | No | Schema defining required inputs |
content_filter | No | Restrictions on searchable content |
research_plan | No | Predefined steps for structured execution |
Basic Template Structure
{
"name": "Company Financial Analysis",
"description": "Comprehensive financial analysis for any public company",
"prompt": "Analyze {{ company_id }} from an investment perspective. Include financial metrics, competitive position, and growth outlook.",
"expected_input": {
"company_id": {
"type": "rp_entity_id"
}
}
}
rp_entity_id
Use for Bigdata entity identifiers (companies, ETFs, etc.):
{
"expected_input": {
"company_id": {"type": "rp_entity_id"},
"competitor_id": {"type": "rp_entity_id"}
}
}
string
Use for free-form text input:
{
"expected_input": {
"topic": {"type": "string"},
"region": {"type": "string"}
}
}
Research {{ topic }} trends in the {{ region }} market.
Focus on key players, regulatory changes, and investment opportunities.
Content Filters
Restrict which sources the research uses:
Filter by Document Type
{
"content_filter": {
"any_of": [
{
"type": "DOCUMENT_TYPE",
"document_types": [
{"type": "TRANSCRIPT", "subtype": "Earnings Call"},
{"type": "FILING"}
]
}
]
}
}
Filter by Source
{
"content_filter": {
"any_of": [
{
"type": "SOURCE_TYPE",
"sources_ids": ["ABC123", "DEF456"]
}
]
}
}
Exclude Specific Content
{
"content_filter": {
"none_of": [
{
"type": "DOCUMENT_TYPE",
"document_types": [
{"type": "NEWS"}
]
}
]
}
}
Available Document Types
| Type | Subtypes |
|---|
TRANSCRIPT | Earnings Call, General Conference Call, Investor Conference Call, etc. |
TRANSCRIPT-PRESENTATION | Same subtypes as TRANSCRIPT |
FILING | RNS-SEC-10-K, RNS-SEC-10-Q, RNS-SEC-8-K, etc. |
NEWS | (no subtypes) |
Research Plans
Add a research plan for structured, step-by-step execution:
{
"research_plan": {
"title": "Comprehensive Credit Analysis",
"steps": [
{"description": "Gather company background and business model"},
{"description": "Analyze recent financial statements and leverage metrics"},
{"description": "Review credit ratings and analyst commentary"},
{"description": "Assess key credit risks and mitigants"},
{"description": "Evaluate liquidity and debt maturity profile"},
{"description": "Formulate investment recommendation"}
]
}
}
When a research_plan is provided, the agent follows your predefined steps for structured, predictable output. Without a plan, the agent dynamically determines research steps based on your prompt.
Complete Example
Here’s a complete template for M&A transaction analysis:
{
"name": "M&A Transaction Analysis",
"description": "Detailed analysis of merger or acquisition transactions",
"prompt": "Analyze the {{ transaction_type }} involving {{ acquirer_id }} and {{ target_id }}. Include:\n\n1. Transaction overview and strategic rationale\n2. Financial terms and valuation analysis\n3. Synergy expectations and integration risks\n4. Regulatory considerations\n5. Market reaction and analyst views\n6. Impact on competitive landscape",
"expected_input": {
"acquirer_id": {"type": "rp_entity_id"},
"target_id": {"type": "rp_entity_id"},
"transaction_type": {"type": "string"}
},
"content_filter": {
"any_of": [
{
"type": "DOCUMENT_TYPE",
"document_types": [
{"type": "NEWS"},
{"type": "FILING"},
{"type": "TRANSCRIPT", "subtype": "Special Situation, M&A and Other"}
]
}
]
},
"research_plan": {
"title": "M&A Analysis Framework",
"steps": [
{"description": "Research transaction details and timeline"},
{"description": "Analyze deal terms and valuation metrics"},
{"description": "Evaluate strategic fit and synergy potential"},
{"description": "Review regulatory filings and antitrust considerations"},
{"description": "Gather analyst reactions and market sentiment"},
{"description": "Synthesize findings and outlook"}
]
}
}
Creating Templates via API
import requests
from dotenv import load_dotenv
import os
load_dotenv()
my_api_key = os.getenv('BIGDATA_API_KEY')
template = {
"name": "Quarterly Earnings Preview",
"description": "Pre-earnings analysis for upcoming quarterly reports",
"prompt": """Prepare an earnings preview for {{ company_id }} ahead of their upcoming quarterly report.
Include:
1. Consensus estimates (revenue, EPS)
2. Key metrics to watch
3. Recent business developments
4. Management guidance and commentary
5. Analyst sentiment and price targets
6. Potential catalysts or risks""",
"expected_input": {
"company_id": {"type": "rp_entity_id"}
},
"content_filter": {
"any_of": [
{
"type": "DOCUMENT_TYPE",
"document_types": [
{"type": "TRANSCRIPT", "subtype": "Earnings Call"},
{"type": "NEWS"}
]
}
]
}
}
response = requests.post(
"https://agents.bigdata.com/v1/workflow/templates",
headers={
"X-API-KEY": my_api_key,
"Content-Type": "application/json"
},
json=template
)
created = response.json()
print(f"Created template: {created['id']}")
print(f"Name: {created['name']}")
Best Practices
- Clear, specific prompts: Include numbered sections or bullet points for structured output
- Appropriate input types: Use
rp_entity_id for entities to enable entity-aware search
- Content filters: Restrict to relevant document types for focused research
- Research plans: Add plans for complex, multi-step analyses
- Descriptive names: Use clear template names for easy identification
- Documentation: Add descriptions explaining the template’s purpose
Next Steps
