Esy Workflow

Research Agent Workflow

A research agent workflow automates the research process: understanding questions, gathering sources, evaluating credibility, and synthesizing findings.

What This Workflow Is

A research agent workflow automates the research process that humans perform when investigating a topic:

  1. Understanding what's being asked
  2. Identifying relevant sources
  3. Gathering information
  4. Evaluating source credibility
  5. Synthesizing findings
  6. Presenting conclusions with citations

The workflow uses multiple specialized agents coordinated through orchestration, with quality gates ensuring reliable outputs.

Inputs and Outputs

Inputs: - Research question or topic - Scope parameters (depth, breadth, time constraints) - Source preferences (academic, news, specific domains) - Output format (summary, detailed report, structured data)

Outputs: - Synthesized findings addressing the question - Source list with credibility assessments - Key quotes and evidence - Confidence levels for claims - Gaps or limitations in available information

Workflow Steps

1. Question Analysis Parse the research question to identify: - Core concepts and entities - Implicit sub-questions - Required scope and depth - Success criteria

2. Search Planning Generate search strategy: - Keywords and queries - Source types to prioritize - Iteration approach

3. Source Gathering Execute searches, collect candidate sources: - Web search - Academic databases - Specialized sources - Evaluate initial relevance

4. Deep Reading For promising sources: - Extract relevant passages - Note key claims and evidence - Identify source credibility signals

5. Synthesis Combine findings: - Identify consensus and conflicts - Weight evidence by source credibility - Form conclusions - Note uncertainty and gaps

6. Output Generation Produce final deliverable: - Structure appropriate to format - Include citations - Highlight confidence levels

Cost and Safety Considerations

Costs: - Search API calls (can be significant at scale) - Document processing (proportional to source count) - Synthesis reasoning (scales with complexity)

Safety considerations: - Source credibility must be assessed, not assumed - Conflicting information should be surfaced, not hidden - Confidence should be calibrated (don't overclaim) - Limitations should be explicit

Mitigations: - Set search budgets to control costs - Use credibility heuristics (domain, publication date, authorship) - Include uncertainty in outputs - Flag low-confidence conclusions for human review